Performance and Scene

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This is the powerpoint presentation "Performance and Scene" that I am presenting at various universities across the country; I consider it the visual accompaniment to my thesis, also titled "Performance and Scene". It concerns classifying users (their scene) based on what they've written about themselves on a profile (their performance).

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Performance and Scene

  1. 1. Brandon Webb, © 2012
  2. 2. PerformanceandSceneUSER CLASSIFICATION PART 1/8 + Humans have a hard time classifying information. Contest Love interest Good vs. Evil Action scenes SCI-FI or WAR? Brandon Webb, © 2012
  3. 3. PerformanceandSceneUSER CLASSIFICATION PART 1/8 + Humans have a hard time classifying information. Advanced Naval/Air/ Technology Land battle Space Travel Evil “Other” Aliens Focus on Focus on military life / utopia / the effects of apocalypse war SCI-FI WAR SCI-FI or WAR? Brandon Webb, © 2012
  4. 4. *Can we sortpeople? Brandon Webb, © 2012
  5. 5. *USER CLASSIFICATIONthe task of sorting people based on the languagethose people deploy in natural language texts. Brandon Webb, © 2012
  6. 6. + Example Natural Language Texts + product reviews (amazon) + status updates (facebook, twitter) +blogs (tumblr) +user profiles (OkCupid, A4A) Brandon Webb, © 2012
  7. 7. +Language about politics< concretethan language about products(Malouf& Mullen, 2008; Pang& Lee, 2007).+Hard to classify users on political forums.(Malouf& Mullen, 2008; Pang& Lee, 2007).WHAT ABOUT ON ADAM4ADAM? Brandon Webb, © 2012
  8. 8. is a public gaydating site.Users create and editprofiles,uploadpics,viewonlinemembers,and send oneanother messages. Brandon Webb, © 2012
  9. 9. *A user’s profile… performance scene Brandon Webb, © 2012
  10. 10. +What is SCENE? Brandon Webb, © 2012
  11. 11. + What is SCENE?+ A4A allows 1-9 scene choices. Brandon Webb, © 2012
  12. 12. + What is SCENE?+ A4A allows 1-9 scene choices.+ Individual identities are socialproducts (Jenkins, 2008). Brandon Webb, © 2012
  13. 13. + What is SCENE?+ A4A allows 1-9 scenes choices.+ Individual identities are social products (Jenkins, 2008).+ Although two users share the same nominal identity, theirlived experience may be entirely different. Brandon Webb, © 2012
  14. 14. PerformanceandSceneSCENE PART 3/8 Gay jock in downtown Gay jock in rural LA. Nebraska Brandon Webb, © 2012
  15. 15. PerformanceandSceneSCENEPART 3/8 Gay jock in downtown Gay jock in rural LA. Nebraska By laying claim to a scene, users communicate that they are more alikethan dislike. Brandon Webb, © 2012
  16. 16. CASUAL“I’d like to think that I’m a fairly unique person, but I guess everyone thinks that about themselves, huh?” Brandon Webb, © 2012
  17. 17. TRENDY“Chill guy here…love photogrphy, art galleries, read a good book in a coffee chop, indie films, fashion magz and clubs.” Brandon Webb, © 2012
  18. 18. ALTERNATIVE“I like to chill with people who are conscious with their world and other people’s worlds. I like people who can carry good conversations and be open minded.” Brandon Webb, © 2012
  19. 19. MILITARY“GL laid back military dude. Into other built guys but not lookin for random hookups.” Brandon Webb, © 2012
  20. 20. JOCK“Looking for sexy athletic hot bodied men for pleasurable times. If you are not athletic we are probably not a good match.” Brandon Webb, © 2012
  21. 21. DRAG“Skater dude by day rock Princess by night. yes I am a drag queen, but don’t let that scare you off it pays the bills goes to show how fun I can be…” Brandon Webb, © 2012
  22. 22. LEATHER“Doctor seeking a young dominant guy to own me. Make me wait on you hand and foot…” Brandon Webb, © 2012
  23. 23. PUNK“Laid back sort of guy. Like other men with similar interests. Not into fem guys at all. Like music and have a soft spot for punk style guys…” Brandon Webb, © 2012
  24. 24. CONSERVATIVE“Regular guy into sports, gym a couple times a week. neg/std free, no drugs, play safe only, looking for similar guys for discreet times or hanging out…” Brandon Webb, © 2012
  25. 25. Brandon Webb, © 2012
  26. 26. PERFORMANCEIntentionalself-construction during jobinterviews, webchatrooms, or datingprofiles.(Goffman, 1959; Sunderland, 1994). Brandon Webb, © 2012
  27. 27. PERFORMPERFORMANCE For whom?Intentionalself-construction during jobinterviews, webchatrooms, or datingprofiles.(Goffman, 1959; Sunderland, 1994). Brandon Webb, © 2012
  28. 28. PerformanceandScenePERFORMANCEPART 4/8 + Users performtheir identity for other users. UNKNOWN TROLL MATCH/FRIEND USER Brandon Webb, © 2012
  29. 29. PerformanceandScenePERFORMANCEPART 4/8 Down for 420, hit me Hey guys, into PNP here up, no ltr If your looking for a one night thing, or into drugs…..no! TROLL USER Brandon Webb, © 2012
  30. 30. PerformanceandScenePERFORMANCEPART 4/8 Navy guy here, be discreet Athletic guy looking for other dl dudes GI bi discreet milguy here Really into other military or jock guys MATCH USER Brandon Webb, © 2012
  31. 31. PerformanceandScenePERFORMANCEPART 4/8 Anybody down for coffee or a PUBLIC movie? Regular guy here love the outdoors! Hey boys, I love hiking and Hey guys the names Rick I’m a basketball music and dance double major… Hey just looking to make some friends Sup! Brandon Webb, © 2012
  32. 32. PerformanceandScenePERFORMANCEPART 4/8 I wanna have sex with someone Love to create fantasy play for watching thru the window boys from 18 to 40 PRIVATE Brandon Webb, © 2012
  33. 33. PerformanceandSceneCORPUSPART 5/8 + 2,437 user profiles were taken from A4A (IRB APPROVAL: 777080). Brandon Webb, © 2012
  34. 34. PerformanceandSceneCORPUSPART 5/8 + 2,437 user profiles were taken from A4A (IRB APPROVAL: 777080). + Each user profile stored in XML file tagged for performance and scene = this became the training corpus. <USER ID=001> <PERFORMANCE> ”Looking for NSA fun. NOT looking for a relationship, already have that” </PERFORMANCE> <SCENE> Casual </SCENE> </USER> … <USER ID=2437> … Brandon Webb, © 2012
  35. 35. PerformanceandSceneCORPUSPART 5/8 + Composition of training corpus 499jock 109military 238alternative577casual 399trendy 41punk 462conservative 92leather 20drag Brandon Webb, © 2012
  36. 36. PerformanceandSceneNAÏVE-BAYESPART 6/8 + How do we classify users? Brandon Webb, © 2012
  37. 37. PerformanceandSceneNAÏVE-BAYESPART 6/8 + How do we classify users? + Each performance is transformed into a list of features so that it can be read by the classifier “Looking for NSA fun. NOT looking for a relationship, already have that. Versatile, but prefer bottom. NO tweekers or PNP losers, been there, was one.” becomes a list of features with functional language deleted… *‘looking’, ‘nsa’, ‘fun’, ‘looking’, ‘relationship’, ‘already’, ‘have’, ‘versatile’, ‘prefer’, ‘bottom’, ‘tweekers’, ‘pnp’, ‘losers’, ‘been’, ‘there’, ‘was’, ‘one’+ Brandon Webb, © 2012
  38. 38. PerformanceandSceneNAÏVE-BAYESPART 6/8 + We do this for all 2,437 profiles so that we end up with a huge list of features. Brandon Webb, © 2012
  39. 39. PerformanceandSceneNAÏVE-BAYESPART 6/8 + We do this for all 2,437 profiles so that we end up with a huge list of features. + Then, for each performance, what features do we witness in that performance that we also witness in the list of features? If a performance has a feature, we mark it with 1. If not, 0. (,contains(‘gear’): 1, contains(‘workout’): 0, contains(‘sup’): 1, …, -, jock) (,contains(‘leather’): 1, contains(‘workout’): 0, contains(‘sup’): 0, …, -, leather) + In this way, each performance becomes a vectorthat we feed to the Naïve-Bayes classifier for training. Brandon Webb, © 2012
  40. 40. PerformanceandSceneNAÏVE-BAYESPART 6/8 NAÏVE-BAYES TRAINING PHASE PSEUDOCODE TRAIN_NBCLASSIFIER (PERFORMANCE, SCENE): 1 F← EXTRACT_ALL_FEATURES(PERFORMANCE, SCENE) 2 V ← TRANSFORM_INTO_VECTOR(PERFORMANCE) 3 For each scene: 4 DO NS← COUNT_SCENE_OCCURENCES(SCENE) 5 PRIOR[S] ← NS/N 6 For each vector in V: 7 For each feature in F: 8 Tscene+feature← COUNT_FEATURE_OCCURENCES(VECTOR) 9 DO CONDPROB[scene][feature]← Tscene+feature/ Σfeature’ * (Tscene+feature’) 10 RETURN (prior, condprob) Brandon Webb, © 2012
  41. 41. PerformanceandSceneNAÏVE-BAYESPART 6/8 NAÏVE-BAYES TESTING PHASE PSEUDOCODE CLASSIFY_USER(PRIOR, CONDPROB, PERFORMANCE): 1 W←EXTRACT_FEATURES(PERFORMANCE) 2 For each scene: 3 DO SCORE[C] ← log(PRIOR[S]) 4 For each feature in W: 5 DO SCORE[S]+= log(CONDPROB[feature][scene]) 6 RETURN ARGMAX(SCORE[S]) Brandon Webb, © 2012
  42. 42. leather ltr dom hivhandcuffs pig bondage hiking btmwstoys gear masculine daddy wildguy dominant hairy workout fems couples sex regular snowboarding poz explore dance pnp mild holes sub bears fats workout water Brandon Webb, © 2012
  43. 43. So how do users performsocial identity? Brandon Webb, © 2012
  44. 44. PerformanceandSceneRESULTSPART 7/8 Naïve-Bayes classifier results (scene vs. scene and multi-scene) Scene CAS TRE ALT MIL JOC LTH PNK DRG CNS CAS - .63 .55 .50 .63 .53 .50 .50 .75 TRE .63 - .60 .50 .73 .53 .50 .50 .78 ALT .55 .60 - .55 .63 .53 .50 .50 .63 MIL .50 .50 .50 - .50 .73 .50 .50 .50 JOC .63 .73 .63 .50 - .53 .50 .50 .73 LTH .53 .53 .53 .73 .53 - .50 .53 .53 PNK .50 .50 .50 .50 .50 .50 - .55 .50 DRG .50 .50 .50 .50 .50 .53 .55 - .50 CNS .75 .78 .63 .50 .73 .53 .50 .50 - ALL .217 Brandon Webb, © 2012
  45. 45. CRAZY RETAIL ARTIST FASHION MOVING MOVED SHOPPING THEATREBEFORE FLOW SHY HOLD SWEET Brandon Webb, © 2012
  46. 46. CRAZY NASTY ARTISTSWEATYFUCKIN CREATIVE SINGER TATTOOS INTENSE LATE BLAH BAR POZ THIN Brandon Webb, © 2012
  47. 47. BROTHERFREAKS NIGGAS BROTHAS LIFTING DRUG SINCERE Brandon Webb, © 2012
  48. 48. CRAZY TRADE SECUREDIVING MILITARY NAVY PARKS FETISH SNOWBOARDING HOLE YO GOVT ARMY PIX Brandon Webb, © 2012
  49. 49. SPORTS TRADE SUPBASKETBALL LIFTING CURIOUS JOCK BUDS GEAR SUM STD PIX Brandon Webb, © 2012
  50. 50. DICKS ANYWAY LICKED VALUES MAKEUPFEM MOVING MOVED SHOPPING FILLED CLUBS WEEKEND CALI CD TX Brandon Webb, © 2012
  51. 51. HOLES DOM EXPLORE WILD COUPLES BONDAGEPIG LEATHER BEARS MILD TOYS FILLED LTRSUB WATER POZ BTM Brandon Webb, © 2012
  52. 52. TEND FASHION ODD PIERCED SERIOUSLY ARTLAIDBACK LATINOS MOMENTSPIERCED LTR WHITES WANNA FOOL HATE Brandon Webb, © 2012
  53. 53. PerformanceandSceneDISCUSSIONPART 8/8 + So what do we know about how users perform social identity? + Users sculpt similarity by appealing to matches and dissimilarity by dissociating from trolls. I’m a well put together & I’m not into GROSS, adjusted 40’s guy. Fun, GAMES, LIARS, educated, Driven, Self CHEATERS/PARTNERED Employed Professional, MEN, or ANONYMOUS Private, Quiet, Focused & SEX. Healthy. MORE LIKE THESE LESS LIKE THESE MATCHES TROLLS Brandon Webb, © 2012
  54. 54. PerformanceandSceneDISCUSSIONPART 8/8 + So what do we know about how users perform social identity? + Users sculpt similarity by appealing to matches and dissimilarity by dissociating from trolls. + Users sculpt identitythrough references to public and private behavior. MORE LIKE THESE LESS LIKE THESE MATCHES TROLLS Brandon Webb, © 2012
  55. 55. PerformanceandSceneDISCUSSIONPART 8/8 MORE LIKE THESE MATCHES + Jocks sculpt similarity through appeals to ACTIVE LIFESTYLES, SPORTS, GYM, FITNESS, and VERNACULARin a public ceremony. Me: 6’ tall, 180 lb, 6% body fat. Loves working out anything I work out 5x a week that challenges me mentally an am a pretty in and physically. shape guyWuz up . . . Lifting&blading Brandon Webb, © 2012
  56. 56. PerformanceandSceneDISCUSSIONPART 8/8 MORE LIKE THESE MATCHES + Leather users sculpt similarity through appeals to NONSTANDARD LIFESTYLES, KINK SEX, andSUBCULTURAL PARAPHERNALIAin a private ceremony. Available to please a guy, worship his body, Feel free to spit on me or following orders. verbally insult me. Bondage, hoods, gags, nipplepl ay. Looking for eager or curious subs and doms. Brandon Webb, © 2012
  57. 57. PerformanceandSceneDISCUSSIONPART 8/8 + When a performance displays behavior that is contradictory of the scene as a category, it is difficult to classify that user. Normal guy, going to work Love gangbangs, anon every day and enjoying life. (blindfolded cool), pump and Love to travel and create dump style fucking. Can get adventures. What’s up with wild also, like ws and light people flipping off others as bondage their primary pic? Brandon Webb, © 2012
  58. 58. PerformanceandSceneDISCUSSIONPART 8/8 + Jocks use VERNACULAR to appeal to matches, whileleather users (if at all) use VERNACULAR to dissociate from trolls. “Don’t sup me, or you will be ignored.” “Sup guys, chill dude here lookin to chat.” Brandon Webb, © 2012
  59. 59. PerformanceandSceneDISCUSSIONPART 8/8 + Jocks use VERNACULAR to appeal to matches, whileleather users (if at all) use VERNACULAR to dissociate from trolls. “Don’t sup me, or you will be ignored.” “Sup guys, chill dude here lookin to chat.” + Due to stereotypes which suggest leather-identified men are unorthodox, some attempt to repair their image through appeals to ACTIVE/STABLE LIFESTYLES and EMPLOYMENT. “I am basically blue collar who works very hard.” “Easy goin, outdoors camp kayak hike bike.” Brandon Webb, © 2012
  60. 60. PerformanceandSceneDISCUSSIONPART 8/8 + Jocks use VERNACULAR to appeal to matches, whileleather users (if at all) use VERNACULAR to dissociate from trolls. “Don’t sup me, or you will be ignored.” “Sup guys, chill dude here lookin to chat.” + Due to stereotypes which suggest leather-identified men are unorthodox, some attempt to repair their image through appeals to ACTIVE/STABLE LIFESTYLES and EMPLOYMENT. “I am basically blue collar who works very hard.” “Easy goin, outdoors camp kayak hike bike.” + Jocks more often than other scenesdissociate from trolls through references to BODY TYPE. “ONLY into guys who r in good shape” “Please be fit if not we probably wont work.” Brandon Webb, © 2012
  61. 61. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. Brandon Webb, © 2012
  62. 62. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. + Naïve-Bayes classifier returned okay results, but failed to capture the subtle complexities of discourse structure. Brandon Webb, © 2012
  63. 63. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. + Naïve-Bayes classifier returned okay results, but failed to capture the subtle complexities of discourse structure. + There are regularities and systematicities to performance that the classifier missed. Brandon Webb, © 2012
  64. 64. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. + Naïve-Bayes classifier returned okay results, but failed to capture the subtle complexities of discourse structure. + There are regularities and systematicities to performance that the classifier missed. + Training on a larger corpus may improve results. Brandon Webb, © 2012
  65. 65. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. + Naïve-Bayes classifier returned okay results, but failed to capture the subtle complexities of discourse structure. + There are regularities and systematicities to performance that the classifier missed. + Training on a larger corpus may improve results. + Tagging each performance for shifts in target audience may improve results. Brandon Webb, © 2012
  66. 66. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. + Naïve-Bayes classifier returned okay results, but failed to capture the subtle complexities of discourse structure. + There are regularities and systematicities to performance that the classifier missed. + Training on a larger corpus may improve results. + Tagging each performance for shifts in target audience may improve results. + Tagging each performance for shifts in discussion of public or private behavior may improve results. Brandon Webb, © 2012
  67. 67. PerformanceandSceneCONCLUSIONFINALE + Tried to classify users on A4A based on performance. + Naïve-Bayes classifier returned okay results, but failed to capture the subtle complexities of discourse structure. + There are regularities and systematicities to performance that the classifier missed. + Training on a larger corpus may improve results. + Tagging each performance for shifts in target audience may improve results. + Tagging each performance for shifts in discussion of public or private behavior may improve results. + Or use other classifiers, like Support Vector Machines. Brandon Webb, © 2012
  68. 68. Brandon Webb, © 2012

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