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List of United States cities by crime rate
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This article needs to be updated. Please update this article to reflect recent events or newly available information. (April 2018)
The following table of United States cities by crime rate is based on Federal Bureau of Investigation Uniform Crime Reports statistics from 2015.[1]
The population numbers are based on U.S. Census estimates for the year end. The number of murders includes nonnegligent manslaughter. This list is based on the reporting. In most cases, the city and the reporting agency are identical. However, in some cases such as Charlotte, Honolulu, and Las Vegas, the reporting agency has more than one municipality.
Murder is the only statistic that all agencies are required to report. Consequently, some agencies do not report all the crimes. If components are missing the total is adjusted to 0.
Contents
[hide]
1 Note about population
2 Crime rates per 100,000 people
3 Criticism of ranking crime data
4 See also
5 References
6 External links
Note about population
Often, one obtains very different results depending on whether crime rates are measured for the city jurisdiction or the metropolitan area.[2]
Information is voluntarily submitted by each jurisdiction and some jurisdictions do not appear in the table because they either did not submit data or they did not meet deadlines.
The FBI website has this disclaimer on population estimates:
For the 2009 population estimates used in this table, the FBI computed individual rates of growth from one year to the next for every city/town and county using 2000 decennial population counts and 2001 through 2009 population estimates from the U.S. Census Bureau. Each agency’s rates of growth were averaged; that average was then applied and added to its 2008 Census population estimate to derive the agency’s 2009 population estimate.[3]
Crime rates per 100,000 people
State
City
Population
Violent Crime
Property Crime
Arson1
Total
Murder and
Nonnegligent Manslaughter
Rape
Robbery
Aggravated Assault
Total
Burglary
Larceny-Theft
Motor Vehicle Theft
New Mexico Albuquerque 559,721 965.8 7.7 72.2 301.2 584.8 6073.2 1071.2 4076.7 925.3 15.9
California Anaheim 349,471 363.7 5.2 36.9 125.6 196.0 2872.3 422.4 1972.4 477.6 8.0
Alaska Anchorage 301,239 1070.9 8.6 171.6 206.1 684.5 3917.5 559.4 2975.0 383.1 35.2
Texas Arlington 387,565 502.1 2.1 53.7 136.5 309.9 3443.6 559.9 2657.1 226.5 7.5
Georgia Atlanta 464,710 1119.6 20.2 36.6 429.3 633.5 5499.3 1028.8 3549.1 921.4 10.8
Colorado Aurora 360,237 460.8 6.7 97.7 124.1 232.3 2936.7 467.2 2119.4 350.0 17.8
Texas Austin 938,728 372.5 2.5 51.9 99.0 219.2 3771.0 532.6 2990.0 248.3 9.7
California Bakersfield 373,887 484.1 5.9 19.0 175.2 284.0 4161.4 1036.9 2484.2 640.3 90.7
Maryland Baltimore 621,252 1535.9 57.8 46.2 694.2 740.1 4980.4 1248.6 2842.3 889.5 41.9
Massachusetts Boston 665,258 706.8 5.7 36.1 233.1 431.9 2316.1 354.3 1769.5 192.3 N/A
New York Buffalo 258,096 1118.6 15.9 67.0 400.2 635.4 4330.2 1076.0 2875.3 378.9 67.0
Arizona Chandler 258,875 189.3 0.4 30.5 44.0 114.3 2083.2 297.4 1686.9 98.9 17.4
North Carolina Charlotte-Mecklenburg 877,817 677.6 6.9 24.6 221.8 424.2 3767.9 769.5 2744.4 253.9 24.6
Illinois Chicago 2,728,695 903.8 23.8 52.5 353.6 480.2 2946.3 482.0 2089.7 374.6 19.6
California Chula Vista 265,215 265.8 2.3 23.8 90.1 149.7 1741.6 267.7 1166.2 307.7 10.2
Ohio Cincinnati 298,478 925.0 22.1 79.1 423.1 400.7 5510.0 1478.5 3642.8 388.6 147.4
Ohio Cleveland* 388,655 1334.3 16.2 124.0 769.3 424.8 5434.4 1787.7 2659.2 987.5 78.2
Colorado Colorado Springs 452,410 438.3 5.5 75.4 83.1 274.3 3648.0 533.6 2732.7 381.7 27.9
Ohio Columbus 860,090 546.3 9.1 95.1 264.2 177.9 3934.3 851.6 2715.6 367.2 47.8
Texas Corpus Christi 324,326 645.0 5.2 86.9 121.5 431.4 3465.6 674.6 2632.8 158.2 18.2
Texas Dallas 1,301,977 694.2 10.4 60.1 320.8 302.8 3440.2 854.2 2002.8 583.3 26.8
Colorado Denver 682,418 673.9 7.8 80.3 180.2 405.6 3529.9 697.8 2192.5 639.6 16.4
Michigan Detroit 673,225 1759.6 43.4 78.7 513.5 1123.5 4093.6 1161.6 2157.2 774.8 125.1
North Carolina Durham 257,911 847.2 13.2 28.7 286.1 519.2 4115.8 1234.5 2644.7 236.5 12.0
Texas El Paso 686,077 366.6 2.5 46.9 59.8 257.4 1914.2 206.8 1591.1 116.3 8.3
Indiana Fort Wayne 259,712 378.9 9.6 37.3 171.7 160.2 3058.4 569.9 2360.7 127.8 18.9
Texas Fort Worth 829,731 525.4 6.7 62.2 118.2 338.2 3585.7 723.7 2589.9 272.1 17.1
California Fresno 520,837 551.2 7.5 32.1 194.3 317.4 4148.3 850.4 2723.3 574.7 49.0
North Carolina Greensboro 285,950 597.0 9.1 25.2 185.3 377.3 3568.5 828.5 2551.5 188.5 34.6
Nevada Henderson 282,554 168.5 1.4 34.7 63.7 68.7 1893.1 479.9 1225.6 187.6 7.1
Hawaii Honolulu 999,307 243.9 1.5 31.8 89.7 120.9 3110.7 428.7 2294.6 387.4 23.1
Texas Houston 2,275,221 966.7 13.3 43.3 451.7 458.3 4397.5 872.8 2928.7 596.0 29.5
Indiana Indianapolis 863,675 1288.0 17.1 78.4 440.2 752.3 4790.8 1283.5 2929.5 577.9 N/A
California Irvine 258,198 55.8 0.8 10.5 22.1 22.5 1498.1 202.6 1217.7 77.8 3.1
Florida Jacksonville 867,258 648.3 11.2 54.3 161.2 421.6 3673.0 701.3 2704.6 267.0 8.2
New Jersey Jersey City 265,159 521.6 10.2 36.6 207.0 267.8 1594.9 368.1 998.6 228.2 23.4
Missouri Kansas City 473,373 1417.3 23.0 77.3 359.8 957.2 4441.3 1029.0 2587.6 824.7 41.8
Texas Laredo 256,280 379.3 3.1 51.9 63.2 261.0 3370.9 405.8 2843.8 121.4 34.3
Nevada Las Vegas 1,562,134 920.7 8.1 70.9 320.7 521.0 2995.3 952.3 1537.0 506.0 8.6
Kentucky Lexington 314,077 332.4 4.8 51.9 162.7 113.0 3949.7 797.6 2834.0 318.1 15.0
Nebraska Lincoln 276,585 370.6 0.4 69.8 77.4 223.1 3265.9 480.1 2655.2 130.5 32.9
California Long Beach 476,318 580.7 7.6 37.2 221.3 314.7 3010.0 649.6 1766.3 594.1 14.5
California Los Angeles 3,962,726 634.8 7.1 55.7 225.9 346.0 2359.6 407.8 1544.2 407.6 28.5
Kentucky Louisville Metro 680,550 631.8 11.9 30.1 227.0 362.8 4166.0 922.3 2769.8 473.9 N/A
Tennessee Memphis 657,936 1740.1 20.5 80.6 475.9 1163.2 5630.8 1561.2 3655.2 414.3 45.9
Arizona Mesa 471,034 418.7 3.4 51.2 86.6 277.5 2527.4 471.1 1881.2 175.1 17.0
Florida Miami 437,969 1021.3 17.1 18.3 383.8 602.1 4367.4 709.9 3132.9 524.7 20.8
Wisconsin Milwaukee 600,400 1596.1 24.2 72.6 624.4 874.9 4264.2 912.9 2122.1 1229.2 37.1
Minnesota Minneapolis 413,479 1062.9 11.4 98.4 458.5 494.6 4193.9 859.8 2918.9 415.3 28.1
Alabama Mobile2 250,346 610.8 9.6 46.3 160.6 394.3 4311.6 882.0 3186.4 243.3 N/A
Tennessee Nashville Metropolitan 658,029 1101.0 10.9 77.0 280.7 732.3 3805.8 779.9 2805.8 220.1 8.1
Louisiana New Orleans 393,447 949.6 41.7 104.0 380.5 423.4 3874.2 736.6 2497.9 639.7 9.1
New York New York 8,537,673 585.8 3.4 14.0 198.2 357.2 1518.7 164.9 1267.4 86.4 N/A
New Jersey Newark* 279,110 1077.7 33.3 17.6 688.6 338.2 2851.2 622.0 1365.1 864.2 14.0
California Oakland 419,481 1442.5 20.3 67.9 784.3 570.0 5856.8 794.6 3539.1 1523.1 42.7
Oklahoma Oklahoma City 630,621 765.6 11.6 76.1 189.0 488.9 3956.1 923.4 2573.3 459.4 14.7
Nebraska Omaha 452,252 515.0 10.6 38.5 144.8 321.1 3595.6 477.6 2555.7 562.3 17.9
Florida Orlando 268,438 940.6 11.9 67.8 194.5 666.4 6015.5 1267.0 4309.0 439.6 14.5
Pennsylvania Philadelphia 1,567,810 1029.0 17.9 84.3 431.5 495.3 3147.4 515.6 2310.7 321.1 21.0
Arizona Phoenix 1,559,744 593.8 7.2 65.1 193.6 327.8 3491.3 820.5 2198.3 472.5 N/A
Pennsylvania Pittsburgh 306,870 706.2 18.6 26.7 279.6 381.3 3224.5 715.9 2312.7 195.8 56.0
Texas Plano 282,968 153.0 1.4 32.2 41.0 78.5 1799.1 260.1 1442.9 96.1 6.7
Oregon Portland* 615,672 472.8 4.2 42.6 137.6 288.5 5234.8 673.4 4013.0 548.3 27.0
North Carolina Raleigh** 428,993 392.3 2.8 18.4 141.0 230.1 3063.0 735.9 2162.7 164.3 12.6
California Riverside 323,064 446.0 3.1 42.4 161.0 239.6 3259.7 505.5 2211.3 542.9 22.0
California Sacramento 489,717 737.4 8.8 21.4 239.7 467.4 3369.5 758.2 2014.4 596.9 28.6
Texas San Antonio 1,463,586 587.2 6.4 71.7 135.7 373.4 5029.5 794.8 3812.8 422.0 17.8
California San Diego 1,400,467 398.6 2.6 40.4 98.4 257.1 2082.0 366.2 1351.9 363.9 12.4
California San Francisco 863,782 776.8 6.1 39.8 417.9 312.9 6138.0 600.4 4737.1 800.5 31.5
California San Jose 1,031,458 329.6 2.9 36.4 110.5 179.8 2427.1 474.7 1273.7 678.7 9.0
California Santa Ana 337,304 482.1 3.6 45.7 155.1 277.8 2155.3 269.5 1332.3 553.5 11.0
Washington Seattle 683,700 598.7 3.4 21.1 224.1 350.2 5522.0 1122.9 3831.9 567.2 13.5
Missouri St. Louis 317,095 1817.1 59.8 82.9 564.5 1110.4 6316.1 1325.2 3998.8 992.1 70.3
Minnesota St. Paul 300,721 703.3 5.3 67.8 237.4 392.7 3282.1 706.6 1994.2 581.3 39.9
Florida St. Petersburg 255,821 741.9 5.5 53.2 224.0 459.3 5622.7 906.5 4120.9 595.3 25.0
California Stockton 304,890 1352.0 16.1 44.3 375.2 916.4 4263.2 948.2 2662.9 652.0 33.8
Florida Tampa 364,383 630.7 9.3 21.1 184.1 416.0 2295.9 503.0 1629.3 163.6 14.8
Ohio Toledo 279,552 1128.9 8.6 81.6 322.7 716.1 4475.0 1476.3 2676.8 321.9 N/A
Arizona Tucson 529,675 655.5 5.9 79.7 199.9 370.0 6642.8 691.7 5586.8 364.2 22.1
Oklahoma Tulsa 401,520 903.6 13.7 90.9 212.7 586.3 5203.2 1372.8 3170.2 660.2 43.3
Virginia Virginia Beach 452,797 138.3 4.2 22.7 59.6 51.7 2205.6 211.1 1898.4 96.1 21.0
District Of Columbia Washington 672,228 1202.6 24.1 73.5 506.4 598.6 4516.2 442.0 3599.1 475.1 N/A
Kansas Wichita 389,824 984.8 6.9 89.5 188.0 700.3 5041.2 892.7 3623.9 524.6 33.1
Notes:
* 2014 Data
* 2013 Data
1 The FBI does not publish arson data unless it receives data from either the agency or the state for all 12 months of the calendar year.
2 The population for the city of Mobile, Alabama, includes 55,819 inhabitants from the jurisdiction of the Mobile County Sheriff's Department.
Criticism of ranking crime data
The FBI web site recommends against using its data for ranking because these rankings lead to simplistic and/or incomplete analyses that often create misleading perceptions adversely affecting cities and counties, along with their residents.[4] The FBI web site also recommends against using its data to judge how effective law enforcement agencies are, since there are many factors that influence crime rates other than law enforcement.[5]
In November 2007, the executive board of the American Society of Criminology (ASC) went further than the FBI itself, and approved a resolution opposing not only the use of the ratings to judge police departments, but also opposing any development of city crime rankings from FBI Uniform Crime Reports (UCRs) at all. The resolution opposed these rankings on the grounds that they "fail to account for the many conditions affecting crime rates" and "divert attention from the individual and community characteristics that elevate crime in all cities", though it did not provide sources or further elaborate on these claims. The resolution states the rankings "represent an irresponsible misuse of the data and do groundless harm to many communities" and "work against a key goal of our society, which is a better understanding of crime-related issues by both scientists and the public".[6]
The U.S. Conference of Mayors passed a similar statement, which also committed the Conference to working with the FBI and the U.S. Department of Justice "to educate reporters, elected officials, and citizens on what the (UCR) data means and doesn't mean."[6]
See also
Shrinking cities in the United States
Crime in the United States
Demographics of the United States
List of U.S. states by homicide rate
Latin American cities by murder rate
List of cities by murder rate
Homicide in world cities
References
Jump up ^ "Crime in the United States by Metropolitan Statistical Area, 2015". FBI. Retrieved 19 February 2017.
Jump up ^ "Crime Rankings 2011-2012". CQ Press.
Jump up ^ "Table 08, Data Declaration - Crime in the United States 2010". Fbi.gov. Retrieved 16 December 2014.
Jump up ^ "Caution Against Ranking". FBI. Retrieved 8 August 2012.
Jump up ^ "A Word About UCR Data". FBI. Archived from the original on 23 September 2010. Retrieved 12 October 2010.
^ Jump up to: a b Criminologists Condemn City crime rankings (November 16, 2008).PRNewswire. Retrieved 13 January 2008.
External links
Murder rate by U.S. state, highest to lowest
[hide]
v
t
e
United States Crime Rates By City Population
250,000 and Above
100,000 to 250,000
60,000 to 100,000
40,000 to 60,000
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text:
Till Death Do Us Part (Cypress Hill album)
From Wikipedia, the free encyclopedia
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For other uses, see 'Til Death Do Us Part (disambiguation).
This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (October 2008) (Learn how and when to remove this template message)
Till Death Do Us Part
North American release cover
Studio album by Cypress Hill
Released
March 23, 2004
Recorded
2002–2004
Genre
Hip hop
Length
48:32
Label
Columbia
Producer
DJ Muggs
The Alchemist
Fredwreck
Cypress Hill chronology
Stash
(2002)Stash2002 Till Death Do Us Part
(2004) Greatest Hits from the Bong
(2005)Greatest Hits from the Bong2005
Alternative cover
The cover used for the edited edition of the album. Also the vinyl release of album and special first pressings with sticker insert of above cover with this being cover of the booklet.
Singles from Till Death Do Us Part
"What's Your Number?"
Released: March 19, 2004
"Latin Thugs"
Released: 2004
Till Death Do Us Part is the seventh studio album by American hip hop group Cypress Hill, released on March 23, 2004 by Columbia Records. This album showed the group introducing reggae elements, especially in the lead single "What's Your Number?", which samples the bass line from the Clash song "The Guns of Brixton." Another song titled "Ganja Bus" features vocals from Damian Marley (son of Bob Marley).
Two different CD covers (artwork) exist: The European and Japanese releases feature the standard sepia version of a picture of a statue of a crucifixion scene. The US CD version includes a free sticker which is a black and white cover with the "old" logo on it. It has a square of thorns and roses around it. This is removable and inserted over the regular cover.
Contents
[hide]
1 Reception
2 Track listing
3 Album singles
4 Personnel
5 Charts
6 References
7 External links
Reception[edit]
Professional ratings
Review scores
Source
Rating
Allmusic [1]
RapReviews.com (8.5/10)[2]
Rolling Stone "[T]he combination of mournful maturity and club-ready fun they come up with on Till Death Do Us Part suits them just fine."[3]
Q magazine "[A] funk-driven return to familiar ground, laced with dark imagery, beefy hooks and sharp vocal trading."[4]
Track listing[edit]
Till Death Do Us Part
No.
Title
Writer(s)
Producer
Length
1. "Another Body Drops" Freese, Muggerud, Reyes DJ Muggs 3:50
2. "Till Death Comes" Freese, Muggerud DJ Muggs 3:30
3. "Latin Thugs" (featuring Tego Calderón) Calderon, Freese, Maman, Reyes The Alchemist 3:46
4. "Ganja Bus" (featuring Damian Marley) Freese, Reyes Tony "CD" Kelly 3:42
5. "Busted in the Hood" Freese, Horowitz, McDaniels, Muggerud, Rubin, Simmons DJ Muggs 4:03
6. "Money" Freese, Muggerud, Reyes DJ Muggs 3:33
7. "Never Know" Freese, Muggerud DJ Muggs 3:14
8. "Last Laugh" (featuring Prodigy and Twin) Bradford, Freese, Johnson, Jones, Muggerud, Raheem, Reyes DJ Muggs 3:42
9. "Bong Hit" Muggerud DJ Muggs 1:20
10. "What's Your Number?" (featuring Tim Armstrong of Rancid) Freese, Muggerud, Paul Simonon DJ Muggs 3:50
11. "Once Again" Freese, Muggerud DJ Muggs 3:48
12. "Number Seven" Muggerud DJ Muggs 0:50
13. "One Last Cigarette" Freese, Muggerud, Piccioni DJ Muggs 2:46
14. "Street Wars" Freese, Muggerud DJ Muggs 2:42
15. "Till Death Do Us Part" Freese, Nassar Fredwreck 3:54
16. "Eulogy" Freese, Muggerud DJ Muggs 1:08
showJapanese CD bonus tracks
No.
Title
Length
17. "Ready To Die" 3:04
18. "Roll It Up Again" 3:16
Album singles[edit]
Single cover
Single information
"What's Your Number?"
Released: March 19, 2004
B-side: "Ready To Die", "Roll It Up"
Personnel[edit]
B-Real - vocals
Sen Dog - vocals
DJ Muggs - producer, executive producer, mixing
Eric Bobo - percussion
The Alchemist - producer, engineer
Tony Kelly - producer
Tim Armstrong - guitar, vocals, guest appearance
Tego Calderón - guest appearance
Damian "Junior Gong" Marley - guest appearance
Prodigy - guest appearance
Fredwreck - guitar, keyboards, moog synthesizer, producer, mixing
Mike Sims - bass, guitar, keyboards, prayers
Rob Hill (producer) - bass, programming, mixing
Rogelio Lozano - guitar, programming
Reggie Stewart - bass, guitar
Tracy Nelson - vocals
Chace Infinite - vocals
Dan Boer - keyboards
Tim "Johnny Vegas" Burton - saxophone
Ray Ramundo - conga
Scott Abels - drums
Al Pahanish - drums
Brian "Big Bass" Gardener - mastering
Robb Episano - photo assistance
Charts[edit]
Album - Billboard (North America)[5]
Year
Chart
Position
2004 The Billboard 200 21
2004 Top R&B/Hip-Hop Albums 23
References[edit]
Jump up ^ Kellman, Andy. "Cypress Hill: Till Death Do Us Part > Review" at AllMusic. Retrieved 22 October 2011.
Jump up ^ Juon, Steve 'Flash' (24 March 2004). "Cypress Hill :: Till Death Do Us Part". RapReview Of The Week. RapReviews.com. Retrieved 22 October 2011.
Jump up ^ "Cypress Hill: Till Death Do Us Part". Rolling Stone. Straight Arrow. 1 April 2004. p. 89. ISSN 0035-791X. Retrieved 22 October 2011.
Jump up ^ "Till Death Do Us Part review". Q. Bauer Media. p. 94. ISSN 0955-4955. Retrieved 22 October 2011.
Jump up ^ "Till Death Do Us Part > Charts & Awards > Billboard Albums" at AllMusic. Retrieved 22 October 2011.
External links[edit]
Cypress Hill – Till Death Do Us Part at Discogs (list of releases)
hide
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Till Death Do Us Part
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Related articles
Discography
Kush (band)
Soul Assassins
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text:
Lookin' Out My Back Door
From Wikipedia, the free encyclopedia
Jump to: navigation, search
"Lookin' Out My Back Door"
Single by Creedence Clearwater Revival
from the album Cosmo's Factory
B-side
"Long As I Can See the Light"
Released
July 25, 1970 (1970-07-25)[1]
Format
7" 45 RPM
Genre
Southern rock
country rock
Length
2:35
Label
Fantasy
Songwriter(s)
John Fogerty
Producer(s)
John Fogerty
Creedence Clearwater Revival singles chronology
"Up Around the Bend"
(1970) "Lookin' Out My Back Door"
(1970) "Have You Ever Seen the Rain?"
(1971)
"Up Around the Bend"
(April 1970) "Lookin' Out My Back Door"
(July 1970) "Have You Ever Seen the Rain?"
(January 1971)
"Lookin' Out My Back Door" is a song recorded by the American band Creedence Clearwater Revival, also known as CCR. The song was written by the band's lead singer, guitarist, and songwriter, John Fogerty. The song is included on their 1970 album Cosmo's Factory, the group's fifth album, which was also their fifth and final number-two Billboard hit.
"Lookin' Out My Back Door" was a direct tribute to the Bakersfield Sound, a form of music that influenced Fogerty and the CCR sound. Buck Owens, one of the architects of the Bakersfield Sound, is even mentioned in the song's lyrics.[citation needed]
Song information[edit]
The song's lyrics, filled with colorful, dream-like imagery, led some to believe that the song was about drugs. According to the drug theory, the "flying spoon" in the song was a reference to a cocaine or heroin spoon, and the crazy animal images were an acid trip. Fogerty, however, has stated in interviews that the song was actually written for his then three-year-old son, Josh. Fogerty has also said that the reference to a parade passing by was inspired by the Dr. Seuss book And to Think That I Saw It on Mulberry Street.[2]
References[edit]
Jump up ^ Tom Hibbert; Jenny Dawson (1990). "Rock '70". In Ashley Brown. The Marshall Cavendish Illustrated History of Popular Music. Volume 12 (Reference ed.). Freeport, New York: Marshall Cavendish. pp. 1342, 1343. ISBN 1-85435-027-7.
Jump up ^ Bordowitz, Hank (1998). Bad Moon Rising: The Unauthorized History of Creedence Clearwater Revival. Chicago Review Press. p. 98.
External links[edit]
Lyrics of this song at MetroLyrics
[hide]
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Willy and the Poor Boys
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Pendulum
Mardi Gras
Live albums
Live in Europe
The Concert
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Creedence Gold
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Chronicle, Vol. 1
The Best of Creedence Clearwater Revival
20 Golden Greats
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At the Movies
Chronicle, Vol. 2
Rollin' on the River
Heartland Music Presents Creedence Clearwater Revival
Keep On Chooglin'
Creedence Clearwater Revival: Box Set
Bad Moon Rising: The Best of Creedence Clearwater Revival
Platinum
Creedence Clearwater Revival Covers the Classics
Singles
"Porterville"/"Call It Pretending"
"Suzie Q. (Part 1)"/"Suzie Q. (Part 2)"
"I Put a Spell on You"/"Walk on the Water"
"Proud Mary"/"Born on the Bayou"
"Bad Moon Rising"/"Lodi"
"Green River"/"Commotion"
"Down on the Corner"/"Fortunate Son"
"Travelin' Band"/"Who'll Stop the Rain"
"Run Through the Jungle"/"Up Around the Bend"
"Lookin' Out My Back Door"/"Long As I Can See the Light"
"Have You Ever Seen the Rain?"/"Hey Tonight"
"Sweet Hitch-Hiker"/"Door to Door"
"Someday Never Comes"/"Tearin' up the Country"
"I Heard It Through the Grapevine"/"Good Golly Miss Molly"
Related articles
Discography
The Blue Velvets
The Golliwogs
Creedence Clearwater Revisited
Recollection
Fogerty v. Fantasy, Inc.
Saul Zaentz
Fantasy Records
Book:Creedence Clearwater Revival
Retrieved from "https://en.wikipedia.org/w/index.php?title=Lookin%27_Out_My_Back_Door&oldid=800657804"
Categories:
Creedence Clearwater Revival songs
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Human–computer interaction
From Wikipedia, the free encyclopedia
Jump to: navigation, search
Human–Computer Interaction (commonly referred to as HCI) researches the design and use of computer technology, focused on the interfaces between people (users) and computers. Researchers in the field of HCI both observe the ways in which humans interact with computers and design technologies that let humans interact with computers in novel ways. As a field of research, human-computer interaction is situated at the intersection of computer science, behavioral sciences, design, media studies, and several other fields of study. The term was popularized by Stuart K. Card, Allen Newell, and Thomas P. Moran in their seminal 1983 book, The Psychology of Human-Computer Interaction, although the authors first used the term in 1980[1] and the first known use was in 1975.[2] The term connotes that, unlike other tools with only limited uses (such as a hammer, useful for driving nails but not much else), a computer has many uses and this takes place as an open-ended dialog between the user and the computer. The notion of dialog likens human-computer interaction to human-to-human interaction, an analogy which is crucial to theoretical considerations in the field.[3][4]
Contents
[hide]
1 Introduction
2 Goals for Computers
3 Differences with related fields
4 Design
4.1 Principles
4.2 Methodologies
5 Display designs
5.1 Thirteen principles of display design
5.1.1 Perceptual principles
5.1.2 Mental model principles
5.1.3 Principles based on attention
5.1.4 Memory principles
6 Human-computer interface
7 Current research
7.1 User customization
7.2 Embedded computation
7.3 Augmented reality
7.4 Social computing
7.5 Knowledge-driven human-computer interaction
7.6 Brain-computer interfaces
8 Factors of change
9 Scientific conferences
10 See also
11 Footnotes
12 Further reading
13 External links
Introduction[edit]
Humans interact with computers in many ways; the interface between humans and computers is crucial to facilitating this interaction. Desktop applications, internet browsers, handheld computers, and computer kiosks make use of the prevalent graphical user interfaces (GUI) of today.[5] Voice user interfaces (VUI) are used for speech recognition and synthesising systems, and the emerging multi-modal and Graphical user interfaces (GUI) allow humans to engage with embodied character agents in a way that cannot be achieved with other interface paradigms. The growth in human-computer interaction field has been in quality of interaction, and in different branching in its history. Instead of designing regular interfaces, the different research branches have had a different focus on the concepts of multimodality rather than unimodality, intelligent adaptive interfaces rather than command/action based ones, and finally active rather than passive interfaces.[citation needed] For instance, more recently, sensors like video cameras and eye trackers can be used to feed physiological information of humans back to computer systems.[6][7] Such information can be used by computers to dynamically adapt content of interfaces. Thus, computers could develop responsiveness to cognitive load[7] and human emotion[6].
The Association for Computing Machinery (ACM) defines human-computer interaction as "a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them".[5] An important facet of HCI is the securing of user satisfaction (or simply End User Computing Satisfaction). "Because human-computer interaction studies a human and a machine in communication, it draws from supporting knowledge on both the machine and the human side. On the machine side, techniques in computer graphics, operating systems, programming languages, and development environments are relevant. On the human side, communication theory, graphic and industrial design disciplines, linguistics, social sciences, cognitive psychology, social psychology, and human factors such as computer user satisfaction are relevant. And, of course, engineering and design methods are relevant."[5] Due to the multidisciplinary nature of HCI, people with a variety of different backgrounds contribute to its success. HCI is also sometimes termed human–machine interaction (HMI), man-machine interaction (MMI) or computer-human interaction (CHI).
Poorly designed human-machine interfaces can lead to many unexpected problems. A classic example of this is the Three Mile Island accident, a nuclear meltdown accident, where investigations concluded that the design of the human-machine interface was at least partly responsible for the disaster.[8][9][10] Similarly, accidents in aviation have resulted from manufacturers' decisions to use non-standard flight instrument or throttle quadrant layouts: even though the new designs were proposed to be superior in basic human-machine interaction, pilots had already ingrained the "standard" layout and thus the conceptually good idea actually had undesirable results.
Goals for Computers[edit]
Human–computer interaction studies the ways in which humans make, or do not make, use of computational artifacts, systems and infrastructures. In doing so, much of the research in the field seeks to improve human-computer interaction by improving the usability of computer interfaces.[11] How usability is to be precisely understood, how it relates to other social and cultural values and when it is, and when it may not be a desirable property of computer interfaces is increasingly debated.[12][13]
Much of the research in the field of human-computer interaction takes an interest in:
Methods for designing novel computer interfaces, thereby optimizing a design for a desired property such as, e.g., learnability or efficiency of use.
Methods for implementing interfaces, e.g., by means of software libraries.
Methods for evaluating and comparing interfaces with respect to their usability and other desirable properties.
Methods for studying human computer use and its sociocultural implications more broadly.
Models and theories of human computer use as well as conceptual frameworks for the design of computer interfaces, such as, e.g., cognitivist user models, Activity Theory or ethnomethodological accounts of human computer use.[14]
Perspectives that critically reflect upon the values that underlie computational design, computer use and HCI research practice.[15]
Visions of what researchers in the field seek to achieve vary. When pursuing a cognitivist perspective, researchers of HCI may seek to align computer interfaces with the mental model that humans have of their activities. When pursuing a post-cognitivist perspective, researchers of HCI may seek to align computer interfaces with existing social practices or existing sociocultural values.
Researchers in HCI are interested in developing new design methodologies, experimenting with new devices, prototyping new software and hardware systems, exploring new interaction paradigms, and developing models and theories of interaction.
Differences with related fields[edit]
This section does not cite any sources. Please help improve this section by adding citations to reliable sources. Unsourced material may be challenged and removed. (February 2013) (Learn how and when to remove this template message)
HCI differs from human factors and ergonomics as HCI focuses more on users working specifically with computers, rather than other kinds of machines or designed artifacts. There is also a focus in HCI on how to implement the computer software and hardware mechanisms to support human–computer interaction. Thus, human factors is a broader term; HCI could be described as the human factors of computers – although some experts try to differentiate these areas.
HCI also differs from human factors in that there is less of a focus on repetitive work-oriented tasks and procedures, and much less emphasis on physical stress and the physical form or industrial design of the user interface, such as keyboards and mouse devices.
Three areas of study have substantial overlap with HCI even as the focus of inquiry shifts. In the study of personal information management (PIM), human interactions with the computer are placed in a larger informational context – people may work with many forms of information, some computer-based, many not (e.g., whiteboards, notebooks, sticky notes, refrigerator magnets) in order to understand and effect desired changes in their world. In computer-supported cooperative work (CSCW), emphasis is placed on the use of computing systems in support of the collaborative work of a group of people. The principles of human interaction management (HIM) extend the scope of CSCW to an organizational level and can be implemented without use of computers.
Design[edit]
Principles[edit]
The user interacts directly with hardware for the human input and output such as displays, e.g. through a graphical user interface. The user interacts with the computer over this software interface using the given input and output (I/O) hardware.
Software and hardware must be matched, so that the processing of the user input is fast enough, the latency of the computer output is not disruptive to the workflow.
When evaluating a current user interface, or designing a new user interface, it is important to keep in mind the following experimental design principles:
Early focus on user(s) and task(s): Establish how many users are needed to perform the task(s) and determine who the appropriate users should be; someone who has never used the interface, and will not use the interface in the future, is most likely not a valid user. In addition, define the task(s) the users will be performing and how often the task(s) need to be performed.
Empirical measurement: Test the interface early on with real users who come in contact with the interface on a daily basis. Keep in mind that results may vary with the performance level of the user and may not be an accurate depiction of the typical human-computer interaction. Establish quantitative usability specifics such as: the number of users performing the task(s), the time to complete the task(s), and the number of errors made during the task(s).
Iterative design: After determining the users, tasks, and empirical measurements to include, perform the following iterative design steps:
Design the user interface
Test
Analyze results
Repeat
Repeat the iterative design process until a sensible, user-friendly interface is created.[16]
Methodologies[edit]
A number of diverse methodologies outlining techniques for human-computer interaction design have emerged since the rise of the field in the 1980s. Most design methodologies stem from a model for how users, designers, and technical systems interact. Early methodologies, for example, treated users' cognitive processes as predictable and quantifiable and encouraged design practitioners to look to cognitive science results in areas such as memory and attention when designing user interfaces. Modern models tend to focus on a constant feedback and conversation between users, designers, and engineers and push for technical systems to be wrapped around the types of experiences users want to have, rather than wrapping user experience around a completed system.
Activity theory: used in HCI to define and study the context in which human interactions with computers take place. Activity theory provides a framework to reason about actions in these contexts, analytical tools with the format of checklists of items that researchers should consider, and informs design of interactions from an activity-centric perspective.[17]
User-centered design: user-centered design (UCD) is a modern, widely practiced design philosophy rooted in the idea that users must take center-stage in the design of any computer system. Users, designers and technical practitioners work together to articulate the wants, needs and limitations of the user and create a system that addresses these elements. Often, user-centered design projects are informed by ethnographic studies of the environments in which users will be interacting with the system. This practice is similar but not identical to participatory design, which emphasizes the possibility for end-users to contribute actively through shared design sessions and workshops.
Principles of user interface design: these are seven principles of user interface design that may be considered at any time during the design of a user interface in any order: tolerance, simplicity, visibility, affordance, consistency, structure and feedback.[18]
Value sensitive design: Value Sensitive Design (VSD) is a method for building technology that account for the values of the people who use the technology directly, as well as those who the technology affects, either directly or indirectly. VSD uses an iterative design process that involves three types of investigations: conceptual, empirical and technical. Conceptual investigations aim at understanding and articulating the various stakeholders of the technology, as well as their values and any values conflicts that might arise for these stakeholders through the use of the technology. Empirical investigations are qualitative or quantitative design research studies used to inform the designers' understanding of the users' values, needs, and practices. Technical investigations can involve either analysis of how people use related technologies, or the design of systems to support values identified in the conceptual and empirical investigations.[19]
Display designs[edit]
Displays are human-made artifacts designed to support the perception of relevant system variables and to facilitate further processing of that information. Before a display is designed, the task that the display is intended to support must be defined (e.g. navigating, controlling, decision making, learning, entertaining, etc.). A user or operator must be able to process whatever information that a system generates and displays; therefore, the information must be displayed according to principles in a manner that will support perception, situation awareness, and understanding.
Thirteen principles of display design[edit]
Christopher Wickens et al. defined 13 principles of display design in their book An Introduction to Human Factors Engineering.[20]
These principles of human perception and information processing can be utilized to create an effective display design. A reduction in errors, a reduction in required training time, an increase in efficiency, and an increase in user satisfaction are a few of the many potential benefits that can be achieved through utilization of these principles.
Certain principles may not be applicable to different displays or situations. Some principles may seem to be conflicting, and there is no simple solution to say that one principle is more important than another. The principles may be tailored to a specific design or situation. Striking a functional balance among the principles is critical for an effective design.[21]
Perceptual principles[edit]
1. Make displays legible (or audible). A display's legibility is critical and necessary for designing a usable display. If the characters or objects being displayed cannot be discernible, then the operator cannot effectively make use of them.
2. Avoid absolute judgment limits. Do not ask the user to determine the level of a variable on the basis of a single sensory variable (e.g. colour, size, loudness). These sensory variables can contain many possible levels.
3. Top-down processing. Signals are likely perceived and interpreted in accordance with what is expected based on a user's experience. If a signal is presented contrary to the user's expectation, more physical evidence of that signal may need to be presented to assure that it is understood correctly.
4. Redundancy gain. If a signal is presented more than once, it is more likely that it will be understood correctly. This can be done by presenting the signal in alternative physical forms (e.g. colour and shape, voice and print, etc.), as redundancy does not imply repetition. A traffic light is a good example of redundancy, as colour and position are redundant.
5. Similarity causes confusion: Use distinguishable elements. Signals that appear to be similar will likely be confused. The ratio of similar features to different features causes signals to be similar. For example, A423B9 is more similar to A423B8 than 92 is to 93. Unnecessarily similar features should be removed and dissimilar features should be highlighted.
Mental model principles[edit]
6. Principle of pictorial realism. A display should look like the variable that it represents (e.g. high temperature on a thermometer shown as a higher vertical level). If there are multiple elements, they can be configured in a manner that looks like it would in the represented environment.
7. Principle of the moving part. Moving elements should move in a pattern and direction compatible with the user's mental model of how it actually moves in the system. For example, the moving element on an altimeter should move upward with increasing altitude.
Principles based on attention[edit]
8. Minimizing information access cost or interaction cost. When the user's attention is diverted from one location to another to access necessary information, there is an associated cost in time or effort. A display design should minimize this cost by allowing for frequently accessed sources to be located at the nearest possible position. However, adequate legibility should not be sacrificed to reduce this cost.
9. Proximity compatibility principle. Divided attention between two information sources may be necessary for the completion of one task. These sources must be mentally integrated and are defined to have close mental proximity. Information access costs should be low, which can be achieved in many ways (e.g. proximity, linkage by common colours, patterns, shapes, etc.). However, close display proximity can be harmful by causing too much clutter.
10. Principle of multiple resources. A user can more easily process information across different resources. For example, visual and auditory information can be presented simultaneously rather than presenting all visual or all auditory information.
Memory principles[edit]
11. Replace memory with visual information: knowledge in the world. A user should not need to retain important information solely in working memory or retrieve it from long-term memory. A menu, checklist, or another display can aid the user by easing the use of their memory. However, the use of memory may sometimes benefit the user by eliminating the need to reference some type of knowledge in the world (e.g., an expert computer operator would rather use direct commands from memory than refer to a manual). The use of knowledge in a user's head and knowledge in the world must be balanced for an effective design.
12. Principle of predictive aiding. Proactive actions are usually more effective than reactive actions. A display should attempt to eliminate resource-demanding cognitive tasks and replace them with simpler perceptual tasks to reduce the use of the user's mental resources. This will allow the user to focus on current conditions, and to consider possible future conditions. An example of a predictive aid is a road sign displaying the distance to a certain destination.
13. Principle of consistency. Old habits from other displays will easily transfer to support processing of new displays if they are designed consistently. A user's long-term memory will trigger actions that are expected to be appropriate. A design must accept this fact and utilize consistency among different displays.
Human-computer interface[edit]
Main article: User interface
The human-computer interface can be described as the point of communication between the human user and the computer. The flow of information between the human and computer is defined as the loop of interaction. The loop of interaction has several aspects to it, including:
Visual Based :The visual based human computer inter-action is probably the most widespread area in HCI(Human Computer Interaction) research.
Audio Based : The audio based interaction between a computer and a human is another important area of in HCI systems. This area deals with information acquired by different audio signals.
Task environment: The conditions and goals set upon the user.
Machine environment: The environment that the computer is connected to, e.g. a laptop in a college student's dorm room.
Areas of the interface: Non-overlapping areas involve processes of the human and computer not pertaining to their interaction. Meanwhile, the overlapping areas only concern themselves with the processes pertaining to their interaction.
Input flow: The flow of information that begins in the task environment, when the user has some task that requires using their computer.
Output: The flow of information that originates in the machine environment.
Feedback: Loops through the interface that evaluate, moderate, and confirm processes as they pass from the human through the interface to the computer and back.
Fit: This is the match between the computer design, the user and the task to optimize the human resources needed to accomplish the task.
Current research[edit]
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Topics in HCI include:
User customization[edit]
End-user development studies how ordinary users could routinely tailor applications to their own needs and use this power to invent new applications based on their understanding of their own domains. With their deeper knowledge of their own knowledge domains, users could increasingly be important sources of new applications at the expense of generic systems programmers (with systems expertise but low domain expertise).
Embedded computation[edit]
Computation is passing beyond computers into every object for which uses can be found. Embedded systems make the environment alive with little computations and automated processes, from computerized cooking appliances to lighting and plumbing fixtures to window blinds to automobile braking systems to greeting cards. To some extent, this development is already taking place. The expected difference in the future is the addition of networked communications that will allow many of these embedded computations to coordinate with each other and with the user. Human interfaces to these embedded devices will in many cases be very different from those appropriate to workstations.
Augmented reality[edit]
Main article: Augmented reality
A common staple of science fiction, augmented reality refers to the notion of layering relevant information into our vision of the world. Existing projects show real-time statistics to users performing difficult tasks, such as manufacturing. Future work might include augmenting our social interactions by providing additional information about those we converse with.
Social computing[edit]
In recent years, there has been an explosion of social science research focusing on interactions as the unit of analysis. Much of this research draws from psychology, social psychology, and sociology. For example, one study found out that people expected a computer with a man's name to cost more than a machine with a woman's name.[22] Other research finds that individuals perceive their interactions with computers more positively than humans, despite behaving the same way towards these machines.[23]
Knowledge-driven human-computer interaction[edit]
In human and computer interactions, there usually exists a semantic gap between human and computer's understandings towards mutual behaviors. Ontology (information science), as a formal representation of domain-specific knowledge, can be used to address this problem, through solving the semantic ambiguities between the two parties.[24]
Brain-computer interfaces[edit]
Main article: Brain-computer interface
Factors of change[edit]
Traditionally, as explained in a journal article discussing user modeling and user-adapted interaction, computer use was modeled as a human-computer dyad in which the two were connected by a narrow explicit communication channel, such as text-based terminals. Much work has been done to make the interaction between a computing system and a human more reflective of the multidimensional nature of everyday communication. However, as stated in the introduction, there is much room for mishaps and failure. Because of these potential issues, human-computer interaction shifted focus beyond the interface to respond to observations as articulated by D. Engelbart: "If ease of use was the only valid criterion, people would stick to tricycles and never try bicycles."[25]
The means by which humans interact with computers continues to evolve rapidly. Human–computer interaction is affected by the forces shaping the nature of future computing. These forces include:
Decreasing hardware costs leading to larger memory and faster systems
Miniaturization of hardware leading to portability
Reduction in power requirements leading to portability
New display technologies leading to the packaging of computational devices in new forms
Specialized hardware leading to new functions
Increased development of network communication and distributed computing
Increasingly widespread use of computers, especially by people who are outside of the computing profession
Increasing innovation in input techniques (e.g., voice, gesture, pen), combined with lowering cost, leading to rapid computerization by people formerly left out of the computer revolution.
Wider social concerns leading to improved access to computers by currently disadvantaged groups
The future for HCI, based on current promising research, is expected[26] to include the following characteristics:
Ubiquitous computing and communication. Computers are expected to communicate through high speed local networks, nationally over wide-area networks, and portably via infrared, ultrasonic, cellular, and other technologies. Data and computational services will be portably accessible from many if not most locations to which a user travels.
High-functionality systems. Systems can have large numbers of functions associated with them. There are so many systems that most users, technical or non-technical, do not have time to learn them in the traditional way (e.g., through thick manuals).
Mass availability of computer graphics. Computer graphics capabilities such as image processing, graphics transformations, rendering, and interactive animation are becoming widespread as inexpensive chips become available for inclusion in general workstations and mobile devices.
Mixed media. Commercial systems can handle images, voice, sounds, video, text, formatted data. These are exchangeable over communication links among users. The separate fields of consumer electronics (e.g., stereo sets, VCRs, televisions) and computers are merging partly. Computer and print fields are expected to cross-assimilate.
High-bandwidth interaction. The rate at which humans and machines interact is expected to increase substantially due to the changes in speed, computer graphics, new media, and new input/output devices. This can lead to some qualitatively different interfaces, such as virtual reality or computational video.
Large and thin displays. New display technologies are finally maturing, enabling very large displays and displays that are thin, lightweight, and low in power use. This is having large effects on portability and will likely enable developing paper-like, pen-based computer interaction systems very different in feel from desktop workstations of the present.
Information utilities. Public information utilities (such as home banking and shopping) and specialized industry services (e.g., weather for pilots) are expected to proliferate. The rate of proliferation can accelerate with the introduction of high-bandwidth interaction and the improvement in quality of interfaces.
Scientific conferences[edit]
One of the main conferences for new research in human-computer interaction is the annually held Association for Computing Machinery's (ACM) Conference on Human Factors in Computing Systems, usually referred to by its short name CHI (pronounced kai, or khai). CHI is organized by ACM Special Interest Group on Computer–Human Interaction (SIGCHI). CHI is a large conference, with thousands of attendants, and is quite broad in scope. It is attended by academics, practitioners and industry people, with company sponsors such as Google, Microsoft, and PayPal.
There are also dozens of other smaller, regional or specialized HCI-related conferences held around the world each year, including:[27]
ASSETS: ACM International Conference on Computers and Accessibility
CSCW: ACM conference on Computer Supported Cooperative Work
CC: Aarhus decennial conference on Critical Computing
DIS: ACM conference on Designing Interactive Systems
ECSCW: European Conference on Computer-Supported Cooperative Work
GROUP: ACM conference on supporting group work
HRI: ACM/IEEE International Conference on Human–robot interaction
HCII: Human-Computer Interaction International
ICMI: International Conference on Multimodal Interfaces
ITS: ACM conference on Interactive Tabletops and Surfaces
MobileHCI: International Conference on Human–Computer Interaction with Mobile Devices and Services
NIME: International Conference on New Interfaces for Musical Expression
OzCHI: Australian Conference on Human-Computer Interaction
TEI: International Conference on Tangible, Embedded and Embodied Interaction
Ubicomp: International Conference on Ubiquitous computing
UIST: ACM Symposium on User Interface Software and Technology
i-USEr: International Conference on User Science and Engineering
INTERACT: IFIP TC13 Conference on Human-Computer Interaction
See also[edit]
Outline of human-computer interaction
Information design
Experience design
Information architecture
Physiological interaction
User experience design
Mindfulness and technology
HCI Bibliography, a web-based project to provide a bibliography of Human Computer Interaction literature
Footnotes[edit]
Jump up ^ Card, Stuart K.; Thomas P. Moran; Allen Newell (July 1980). "The keystroke-level model for user performance time with interactive systems". Communications of the ACM. 23 (7): 396–410. doi:10.1145/358886.358895.
Jump up ^ Carlisle, James H. (June 1976). "Evaluating the impact of office automation on top management communication". Proceedings of the June 7–10, 1976, National Computer Conference and Exposition. pp. 611–616. doi:10.1145/1499799.1499885. Use of 'human-computer interaction' appears in references Missing or empty |url= (help)
Jump up ^ Suchman, Lucy (1987). Plans and Situated Action. The Problem of Human-Machine Communication. New York, Cambridge: Cambridge University Press. Retrieved 7 March 2015.
Jump up ^ Dourish, Paul (2001). Where the Action Is: The Foundations of Embodied Interaction. Cambridge, MA: MIT Press.
^ Jump up to: a b c Hewett; Baecker; Card; Carey; Gasen; Mantei; Perlman; Strong; Verplank. "ACM SIGCHI Curricula for Human-Computer Interaction". ACM SIGCHI. Retrieved 15 July 2014.
^ Jump up to: a b D, Fehrenbacher, Dennis (2017). "Affect Infusion and Detection through Faces in Computer-mediated Knowledge-sharing Decisions". Journal of the Association for Information Systems. 18 (10). ISSN 1536-9323 – via https://dennisfehrenbacher.files.wordpress.com/2013/09/fehrenbacher-2017-affect-infusion-and-detection-through-faces-in-computer-mediated-jais-published.pdf.
^ Jump up to: a b Fehrenbacher, Dennis D.; Djamasbi, Soussan (2017-05-01). "Information systems and task demand: An exploratory pupillometry study of computerized decision making". Decision Support Systems. 97 (Supplement C): 1–11. doi:10.1016/j.dss.2017.02.007.
Jump up ^ Ergoweb. "What is Cognitive Ergonomics?". Ergoweb.com. Retrieved August 29, 2011.
Jump up ^ "NRC: Backgrounder on the Three Mile Island Accident". Nrc.gov. Retrieved August 29, 2011.
Jump up ^ http://www.threemileisland.org/downloads/188.pdf
Jump up ^ Grudin, Jonathan (1992). "Utility and usability: research issues and development contexts". Interacting with Computers. 4 (2): 209–217. doi:10.1016/0953-5438(92)90005-z. Retrieved 7 March 2015.
Jump up ^ Chalmers, Matthew; Galani, Areti. "Seamful interweaving: heterogeneity in the theory and design of interactive systems". Procee ' ]p[p plluuykk ] [jioopji[dings of the 5th conference on Designing interactive systems: processes, practices, methods, and techniques: 243–252. Retrieved 7 March 2015. line feed character in |journal= at position 7 (help)
Jump up ^ Barkhuus, Louise; Polichar, Valerie E. (2011). "Empowerment through seamfulness: smart phones in everyday life". Personal and Ubiquitous Computing. 15 (6): 629–639. doi:10.1007/s00779-010-0342-4. Retrieved 7 March 2015.
Jump up ^ Rogers, Yvonne (2012). "HCI Theory: Classical, Modern, and Contemporary". Synthesis Lectures on Human-Centered Informatics. 5: 1–129. doi:10.2200/S00418ED1V01Y201205HCI014. Retrieved 7 March 2015.
Jump up ^ Sengers, Phoebe; Boehner, Kirsten; David, Shay; Joseph, Kaye. "Reflective Design". CC '05 Proceedings of the 4th decennial conference on Critical computing: between sense and sensibility. 5: 49–58. Retrieved 7 March 2015.
Jump up ^ Green, Paul (2008). Iterative Design. Lecture presented in Industrial and Operations Engineering 436 (Human Factors in Computer Systems, University of Michigan, Ann Arbor, MI, February 4, 2008.
Jump up ^ Kaptelinin, Victor (2012): Activity Theory. In: Soegaard, Mads and Dam, Rikke Friis (eds.). "Encyclopedia of Human-Computer Interaction". The Interaction-Design.org Foundation. Available online at http://www.interaction-design.org/encyclopedia/activity_theory.html
Jump up ^ "The Case for HCI Design Patterns".
Jump up ^ Friedman, B., Kahn Jr, P. H., Borning, A., & Kahn, P. H. (2006). Value Sensitive Design and information systems. Human-Computer Interaction and Management Information Systems: Foundations. ME Sharpe, New York, 348–372.
Jump up ^ Wickens, Christopher D., John D. Lee, Yili Liu, and Sallie E. Gordon Becker. An Introduction to Human Factors Engineering. Second ed. Upper Saddle River, NJ: Pearson Prentice Hall, 2004. 185–193.
Jump up ^ Brown, C. Marlin. Human-Computer Interface Design Guidelines. Intellect Books, 1998. 2–3.
Jump up ^ Posard, Marek (2014). "Status processes in human-computer interactions: Does gender matter?". Computers in Human Behavior. 37 (37): 189–195. doi:10.1016/j.chb.2014.04.025.
Jump up ^ Posard, Marek; Rinderknecht, R. Gordon (2015). "Do people like working with computers more than human beings?". Computers in Human Behavior. 51: 232–238. doi:10.1016/j.chb.2015.04.057.
Jump up ^ Dong, Hai; Hussain, Farookh; Elizabeth, Chang. "A human-centered semantic service platform for the digital ecosystems environment". World Wide Web. 13 (1-2): 75–103.
Jump up ^ Fischer, Gerhard (1 May 2000). "User Modeling in Human–Computer Interaction". User Modeling and User-Adapted Interaction. 11 (1-2): 65–86. Retrieved 3 November 2016.
Jump up ^ SINHA, Gaurav; SHAHI, Rahul; SHANKAR, Mani. Human Computer Interaction. In: Emerging Trends in Engineering and Technology (ICETET), 2010 3rd International Conference on. IEEE, 2010. p. 1-4.
Jump up ^ "Conference Search: hci". www.confsearch.org.
Further reading[edit]
Academic overviews of the field
Julie A. Jacko (Ed.). (2012). Human-Computer Interaction Handbook (3rd Edition). CRC Press. ISBN 1-4398-2943-8
Andrew Sears and Julie A. Jacko (Eds.). (2007). Human-Computer Interaction Handbook (2nd Edition). CRC Press. ISBN 0-8058-5870-9
Julie A. Jacko and Andrew Sears (Eds.). (2003). Human-Computer Interaction Handbook. Mahwah: Lawrence Erlbaum & Associates. ISBN 0-8058-4468-6
Historically important classic[citation needed]
Stuart K. Card, Thomas P. Moran, Allen Newell (1983): The Psychology of Human–Computer Interaction. Erlbaum, Hillsdale 1983 ISBN 0-89859-243-7
Overviews of history of the field
Jonathan Grudin: A moving target: The evolution of human–computer interaction. In Andrew Sears and Julie A. Jacko (Eds.). (2007). Human-Computer Interaction Handbook (2nd Edition). CRC Press. ISBN 0-8058-5870-9
Myers, Brad (1998). "A brief history of human–computer interaction technology". Interactions. 5 (2): 44–54. doi:10.1145/274430.274436.
John M. Carroll: Human Computer Interaction: History and Status. Encyclopedia Entry at Interaction-Design.org
Carroll, John M. (2010). "Conceptualizing a possible discipline of human–computer interaction". Interacting with Computers. 22 (1): 3–12. doi:10.1016/j.intcom.2009.11.008.
Sara Candeias, S. and A. Veiga The dialogue between man and machine: the role of language theory and technology, Sandra M. Aluísio & Stella E. O. Tagnin, New Language Technologies and Linguistic Research, A Two-Way Road: cap. 11. Cambridge Scholars Publishing. (ISBN 978-1-4438-5377-4)
Social science and HCI
Nass, Clifford; Fogg, B. J.; Moon, Youngme (1996). "Can computers be teammates?". International Journal of Human-Computer Studies. 45 (6): 669–678. doi:10.1006/ijhc.1996.0073.
Nass, Clifford; Moon, Youngme (2000). "Machines and mindlessness: Social responses to computers". Journal of social issues. 56 (1): 81–103. doi:10.1111/0022-4537.00153.
Posard, Marek N (2014). "Status processes in human-computer interactions: Does gender matter?". Computers in Human Behavior. 37: 189–195. doi:10.1016/j.chb.2014.04.025.
Posard, Marek N.; Rinderknecht, R. Gordon (2015). "Do people like working with computers more than human beings?". Computers in Human Behavior. 51: 232–238. doi:10.1016/j.chb.2015.04.057.
Academic journals
ACM Transactions on Computer-Human Interaction
Behaviour & Information Technology [1]
Interacting with Computers
International Journal of Human-Computer Interaction
International Journal of Human-Computer Studies
Human-Computer Interaction [2] [3]
Collection of papers
Ronald M. Baecker, Jonathan Grudin, William A. S. Buxton, Saul Greenberg (Eds.) (1995): Readings in human–computer interaction. Toward the Year 2000. 2. ed. Morgan Kaufmann, San Francisco 1995 ISBN 1-55860-246-1
Mithun Ahamed, Developing a Message Interface Architecture for Android Operating Systems, (2015). [4]
Treatments by one or few authors, often aimed at a more general audience
Jakob Nielsen: Usability Engineering. Academic Press, Boston 1993 ISBN 0-12-518405-0
Donald A. Norman: The Psychology of Everyday Things. Basic Books, New York 1988 ISBN 0-465-06709-3
Jef Raskin: The Humane Interface. New directions for designing interactive systems. Addison-Wesley, Boston 2000 ISBN 0-201-37937-6
Bruce Tognazzini: Tog on Interface. Addison-Wesley, Reading 1991 ISBN 0-201-60842-1
Textbooks
Alan Dix, Janet Finlay, Gregory Abowd, and Russell Beale (2003): Human–Computer Interaction. 3rd Edition. Prentice Hall, 2003. http://hcibook.com/e3/ ISBN 0-13-046109-1
Yvonne Rogers, Helen Sharp & Jenny Preece: Interaction Design: Beyond Human–Computer Interaction, 3rd ed. John Wiley & Sons Ltd., 2011 ISBN 0-470-66576-9
Helen Sharp, Yvonne Rogers & Jenny Preece: Interaction Design: Beyond Human–Computer Interaction, 2nd ed. John Wiley & Sons Ltd., 2007 ISBN 0-470-01866-6
Matt Jones (interaction designer) and Gary Marsden (2006). Mobile Interaction Design, John Wiley and Sons Ltd.
External links[edit]
Wikimedia Commons has media related to Human-computer interaction.
Bad Human Factors Designs
The HCI Wiki Bibliography with over 100,000 publications.
The HCI Bibliography Over 100,000 publications about HCI.
Human-Centered Computing Education Digital Library
HCI Webliography
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