A"Twi&er)Based"Study"of"" Newly"Formed"Clippings"" in"American"English" ! ! Sravana!Reddy,!Joy!Zhong,!James!Stanford! Dartmouth!College!
Previous!Work! Baclawski!(2012)! A!study!of!Fs!(‘adorbs’)!in!40!TwiLer!users!
Research!QuesNons! • Are!these!clippings!just!cyclical!“slang”?!(Eble!1996,! 2004)! ! • Are!they!an!increasingly!producNve!process!with!new! social!meanings?! ! • Is!this!type!of!clipping!more!producNve!than!past! generaNons?! ! • What!is!the!role!of!the!–s!suffix!( adorbs,(awks,(totes )?! ! • Which!speakers!use!it!the!most?!Age,!gender,!ethnicity?!
This!Study! Hypothesis :!! Women !are!leading!in!the!usage!of! these!new!clippings,!and!it!is!more! urban/suburban" than!rural! Labov!(1990,!2001),!Trudgill!(1972),!Coates!&!Pichler!(2011),!Holmes! &!Meyerhoff!(2003),!Wolfram!&!SchillingFEstes!(2006:155F6)!
Why!use!TwiLer!for!! American!Dialect!Research?! Each!era!applied!contemporary!technology… ! – Kurath!(1939)! – Hanley’s!recordings!(1931F1937)!(Purnell!2012)! – Chambers!&!Trudgill!(1998)! – Labov,!Ash!&!Boberg!(2006)! – Kretzschmar!(2009)! and!many!more !! Now :!Social!Media!analysis,! computaNonal!modeling,!! Mechanical!Turk!
TwiLer!for!SociolinguisNcs! – Eisenstein,!O’Connor,!Smith!&!Xing!(2010)! US!regional!variaNon!in!lexical!items! – Bamman,!Eisenstein!&!Schnoebelen!(2012)! Gendered!language!and!networks! – Maybaum!(2012)!! TwiLer!terms! – Zappavigna!(2013)!! TwiLer!discourse!and!variaNon! – Doyle!(2014)! Geographic!distribuNon!of!“needs!done”!
Methodology! • Collected!185!million!geoFtagged!tweets ( originaNng!in!the!US!(JulFNov!2013)!! by!893,024!users! • AutomaNcally!extracted!a!list!of!clippings!! • For!each!word,!created!demographic!profile!of! users!! – Gender! – PopulaNon,!median!age,!and!ethnic!distribuNon!at! the!user’s!locaNon! • Compared!demographic!features!of!clipping! and!its!original!form!
ExtracNng!Clippings! • Rather!than!manually!compiling!list!of! clippings,!automaNcally!learn!from!TwiLer!data! • A!clipping!and!its!original!form!will!be!used!in! roughly!similar!contexts!
ExtracNng!Clippings! • Represent!every!word! totes! leo:!am,!are,!was,!were,!is..! type!as!vector!of!its!leo! right:!okay,!ok,!adorbs,!fine…! ! and!right!context! adorable! leo:!is,!so,!these,!looks…! • Rank!every!word!pair!by! right:!omg,!with,!dork,…! ! context!vector!similarity!! totally! leo:!am,!are,!was,!were,!is…! • Extract!top!ranked!pairs! right:!okay,!fine,!insane,!not…! ! where!first!three! ! characters!match!
Old!vs.!New!Clippings! • Survey!on!Mechanical!Turk!! • Demographic!quesNons:!age,!gender,!locaNon!! • Rate!familiarity!with!each!clipping! o Unfamiliar! o Familiar,!but!I!do!not!use!it! o I!use!it!in!speech!only! o I!use!it!in!wriNng!only! o I!use!it!in!speech!and!wriNng! • Same!survey!also!conducted!with!Dartmouth! undergraduate!students!
Old!vs.!New!Clippings! • Split!survey!respondents!into!ages!18F29!and!30+! • For!each!clipping,!compute!average!familiarity! score!within!the!two!age!groups! ! 4.72 4.25 4.14 0!=!Unfamiliar! 3.75 Avg8Familiarity8Score 3.6 3!=!Familiar,!but!I!do! not!use!it! Over830 1.94 4!=!I!use!it!in!speech! Under830 1.52 1.13 only! 0.89 0.76 5!=!I!use!it!in!wriNng! only! 6!=!I!use!it!in!speech! sesh obvi perf probs totes and!wriNng ! Top858New8Words
Old!vs.!New!Clippings! • Newness!score!for!clipping!! =!below!30!familiarity!–!above!30!familiarity! ! 4.72 4.25 4.14 3.75 Avg8Familiarity8Score 3.6 Over830 1.94 Under830 1.52 1.13 0.89 0.76 sesh obvi perf probs totes Top858New8Words
Old!vs.!New!Clippings! • Newness!score!for!clipping!! =!below!30!familiarity!–!above!30!familiarity! • Threshold!at!1.0!newness!score! -2 -1 0 1 2 3 cig! choc! doc! perv! frat! vid! alc! vom! ridic! adorbs! perf! sesh! Old!clippings!(55)! New!clippings!(25)!
Old!vs.!New!Clippings! cig! choc! perv! frat! vid! alc! vom! ridic! adorbs! perf! sesh! doc! chem! esp! apps! delish! obvi! perv! undies! parm! def! intro! cray! pregs! defly! probs! prolly! convo! prez! adorb! comfy! champ! prac! sus! choreo! gents! hilar! totes! prep! merch! pedi! info! secs! gorg! lolly! presh! pic! preggo! approx! vacay! guac! anon! craycray! cig! sched! fave! roomie! breaky! vocab! fams! chiro! prob! milli! liq! ortho! mins! obv! McD’s! collab! sibs! taL! diff! fam! preg! num! combo! meds! defs! calc! Old!clippings!(55)! New!clippings!(25)!
Clippings!on!TwiLer! Number!of!users! 900000! 900000! 800000! 800000! 700000! 700000! 600000! 600000! 500000! 500000! 400000! 400000! 300000! 300000! 200000! 200000! 100000! 100000! 0! 0! Clipping! Original! Clipping! Original! New! Old!
Demographic!Analysis! • Gender! (following!Bamman!et!al.) ! – Most!TwiLer!users!report!a!name!in!addiNon!to! their!pseudonym! ! ! ! – Match!first!name!against!the!Social!Security! AdministraNon!list!of!baby!names!born!in!1995! – About!2/3!of!users!have!names!in!the!SSA!list!and! are!assigned!a!gender!
Demographic!Analysis! • LocaNon!! (following!Eisenstein!et!al.)! – Tweets!are!geoFtagged!with!laNtude/longitude! – Map!each!geoFcoordinate!to!one!of!33000!! Zip!Code!TabulaNon!Areas!(ZCTAs)! – Ignore!users!that!tweet!from!more!than!one!ZCTA! – Get!demographic!aLributes!of!ZCTAs!from!2010! Census:!PopulaNon,!Median!Age,!White%,!African! American%,!Asian%,!NaNve!American%,!Hispanic%! – Each!user!is!now!associated!with!a!demographic! profile!of!their!environment!
Demographic!Analysis! • LogisNc!regression! – Predicted!variable:!clipping!or!original?! – Features:!demographic!profile!of!users!! • Gender! • PopulaNon! • Median!Age! • Ethnicity!
New!and!Old!Clippings! Gender!Female! Log10!PopulaNon! New! Old! New! Old! 0.1! 0.035! 0.03! 0.05! Log!odds! 0.025! Log!odds! Log!odds! 0! 0.02! 0.015! F0.05! All!factors! 0.01! shown! are!! F0.1! significant! 0.005! (p<0.05)! 0! F0.15!
New!and!Old!Clippings! Median!Age! Ethnicity! New! Old! 0.005! 0.004! 0.003! Log!odds! 0.002! Log!odds! 0.001! No!Significant!Effects! 0! F0.001! F0.002! F0.003! F0.004! F0.005!
Usage!of!Fs!suffix!in!clippings! Gender!Female! Median!Age! 0.6! 0! adorbs/adorb,! F0.002! 0.5! probs/prob,! fams/fam,! F0.004! awks/awk,! Log!odds! Log!odds! 0.4! pregs/preg,! F0.006! defs/def! ! 0.3! F0.008! F0.01! 0.2! F0.012! 0.1! F0.014! 0! F0.016!
Conclusion! Hypothesis(Confirmed :!! Women !are!leading!in!the!usage!of! these!new!clippings,!and!it!is!more! urban/suburban" than!rural!
Are!clippings!a!TwiLer!arNfact?! They!abound!in!longFform!blog!posts!too…! …!and!TwiLer!users!ooen!lengthen!words!
Are!clippings!a!TwiLer!arNfact?! Baldwin!et!al.!(2013)!measure!average!word!lengths! in!TwiLer!and!different!corpora!
Are!clippings!a!TwiLer!arNfact?! Eisenstein!et!al.!(2013)!find!shortened!forms!! are!mainly!used!in!tweets!of!length!much!less!than!! 140!characters.!Shortening!is!not!used!in!order!to!! fit!length!constraints!!
Are!clippings!a!TwiLer!arNfact?! Our!experiment:!avg!lengths!of!tweets!containing!! clippings!compared!to!tweets!with!original!forms! 140! 140! 120! 120! 100! 100! 80! 80! 60! 60! 81.64! 40! 40! 77.01! 20! 20! 65.08! 73.74! 0! 0! Clipping! Original! Clipping! Original! New! Old!
Future!Work! • Track!spread!of!clippings!in!TwiLer!over!Nme! – Will!these!clippings!spread!throughout!the! populaNon?! – Geographic/demographic!dimensions!of!spread?! – When!did!these!clippings!originate?!! ! • MorphoFphonological!study!of!clippings! !
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