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Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter
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Meaning as Collective Use: Predicting Semantic Hashtag Categories on Twitter

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Presentation of our best paper work at MSM 2013 at WWW 2013.

Presentation of our best paper work at MSM 2013 at WWW 2013.

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  • 1. TU Graz - Knowledge Management Institute1Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseMeaning as Collective Use:Predicting Semantic Hashtag Categories on TwitterLisa Posch, Claudia Wagner, Philipp Singer, Markus StrohmaierKnowledge Management Institute and Know CenterGraz University of Technology, Austria
  • 2. TU Graz - Knowledge Management Institute2Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseMotivationTwitterContentPragmatics?
  • 3. TU Graz - Knowledge Management Institute3Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseSemantic Hashtag CategoryHashtagsSemantic Category?Conference?Meaning is use [Wittgenstein]Content: narrow lexical context of a wordMeaning of a word is defined by the variety of uses to which the word is putPragmatics of a word – how a hashtag is used by a large group of usersPolitics?Technology?
  • 4. TU Graz - Knowledge Management Institute4Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UsePragmatics• structural patterns of social connections• Is the stream consumed by the same users that contribute to it?• Are social connections distributed evenly?• How much do the patterns change over time?• ...• the structural context in which a hashtag occurs• How democratically is a hashtag used?• How conversational are tweets of a hashtag stream?• ...
  • 5. TU Graz - Knowledge Management Institute5Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseResearch Questions1. Do different semantic categories of hashtags revealsubstantially different usage patterns?2. To what extent do pragmatic and lexical propertiesof hashtags help to predict the semantic category ofa hashtag?
  • 6. TU Graz - Knowledge Management Institute6Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseDataset Twitter Semantic categories[Romero et al.]technology gamesidioms musicsports celebritypolitical movies#factaboutme#followfriday#dontyouhate #iloveitwhen#nevertrust#iwish #omgfacts#oneofmyfollowers#rememberwhen#wheniwaslittleD. M. Romero, B. Meeder, and J. Kleinberg. Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on Twitter. In Proceedingsof the 20th international conference on World wide web, WWW 11, pages 695{704, New York, NY, USA, 2011. ACM.
  • 7. TU Graz - Knowledge Management Institute7Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseDataset three parts time frames of four weeks hashtag stream tweets social structure of authorsD. M. Romero, B. Meeder, and J. Kleinberg. Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on Twitter. In Proceedingsof the 20th international conference on World wide web, WWW 11, pages 695{704, New York, NY, USA, 2011. ACM.Static features Dynamicfeatures
  • 8. TU Graz - Knowledge Management Institute8Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseFeatures Static Pragmatic Measures author, follower, followee, friend entropies measure democracy of distributions author-follower, -followee, -friend overlaps measures if stream is consumed and produced by same users informational, hashtag, retweet, conversational coverages measures the nature of messages Dynamic Pragmatic Measures symmetric KL divergence for authors, followers, followees, friends measure how stable the social structure of a stream is Lexical Measure term frequency
  • 9. TU Graz - Knowledge Management Institute9Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseDo different semantic categories ofhashtags reveal substantially differentusage patterns?
  • 10. TU Graz - Knowledge Management Institute10Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseUsage Patterns Pragmatic fingerprints Differences between categories Statistically significant? Pairwise comparison of categories Mann-Whitney-Wilcoxon-Test
  • 11. TU Graz - Knowledge Management Institute11Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseResults: Usage Patterns With p < 0.05: 26 statistical significances Best distinguishable categories: idioms, technology Most discriminative features: informational coverage,KL divergences for followers, authors, and friends
  • 12. TU Graz - Knowledge Management Institute12Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseResults: Usage Patterns
  • 13. TU Graz - Knowledge Management Institute13Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UsePreliminary observations Pragmatic features can help to distinguish semanticcategories Idioms and technology exhibit more distinct usagepatterns than other semantic categories Informational coverage and KL divergence are themost discriminative features
  • 14. TU Graz - Knowledge Management Institute14Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseTo what extent do pragmatic and lexicalproperties of hashtags help to predict thesemantic category of a hashtag?
  • 15. TU Graz - Knowledge Management Institute15Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseHashtag Prediction Classify temporal snapshots of hashtag streams intotheir correct semantic categories By analyzing how they are used over time Extremely Randomized Trees Stratified 6-fold Cross Validation Baseline (randomly permuted categories 100 times)
  • 16. TU Graz - Knowledge Management Institute16Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseHashtag Prediction Models Static Pragmatic Dynamic Pragmatic Combined Pragmatic Lexical Combined Pragmatic and Lexical
  • 17. TU Graz - Knowledge Management Institute17Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseResults: Hashtag Prediction
  • 18. TU Graz - Knowledge Management Institute18Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseResults: Hashtag Prediction Feature Ranking Information Gain1. Informational coverage2. KL divergence followers3. KL divergence friends4. Hashtag coverage5. Friend entropy
  • 19. TU Graz - Knowledge Management Institute19Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseDiscussion Lexical features perform better But lexical features exhibit limitations text and language dependent only for settings with textual content Pragmatic features have advantages rely on usage information independent of the type of content may also be computed for social video or image streams multi-language corpora
  • 20. TU Graz - Knowledge Management Institute20Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseConclusions & Implications Collective usage of hashtags reveals informationabout their semantics Further insights necessary; especially for domainswhere no textual content is available Pragmatic features can supplement lexical features
  • 21. TU Graz - Knowledge Management Institute21Philipp Singer Rio de Janeiro, 2013-05-13 Meaning as Collective UseThanks for your attention!Pragmatic features can play a vital role insupplementing or replacing lexical features!

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