Resources

This page is in progress. Suggestions are welcome!

Computational sociolinguistics (general)

• Computational Sociolinguistics: A Survey, Nguyen et al., Computational Linguistics. Vol. 42, No. 3, Pages 537-593 (2016). Survey article. The tutorial will build on this article and extend the material by also including recently published papers.
• What to do about bad language on the internet, Eisenstein, NAACL (2013). Makes a good case why language variation is interesting and reflects on the NLP community's response.

Language and Social Identity

Prediction of social variables

• A latent variable model for geographic lexical variation. Eisenstein et al., EMNLP 2010.
• Automatically categorizing written texts by author gender. Koppel et al., Literary and Linguistic Computing, 2002.
• Developing age and gender predictive lexica over social media. Sap et al., EMNLP 2014
• Gender attribution: Tracing stylometric evidence beyond topic and genre. Sarawgi et al., CoNLL 2011.
• "How old do you think I am?" A study of language and age in Twitter. Nguyen et al., ICWSM 2013.
• Personality, gender, and age in the language of social media: The open-vocabulary approach. Schwartz. et al., PLoS ONE, 2013.

Papers that take a critical look at operationalization of gender in NLP

• Gender as a variable in natural-language processing: ethical considerations. Larson, Proceedings of the First Workshop on Ethics in Natural Language Processing, 2017.
• Gender identity and lexical variation in social media. Bamman et al., Journal of Sociolinguistics, 2014.
• These are not the stereotypes you are looking for: bias and fairness in authorial gender attribution. Koolen and van Cranenburgh, Proceedings of the First Workshop on Ethics in Natural Language Processing, 2017.
• User demographics and language in an implicit social network. Filippova, EMNLP-CoNLL 2012.
• Why gender and age prediction from tweets is hard: Lessons from a crowdsourcing experiment. Nguyen et al., COLING 2014.

Improving NLP tools by accounting for language variation

• Demographic factors improve classification performance. Hovy, ACL-IJCNLP 2015.
• Exploring demographic language variations to improve multilingual sentiment analysis in social media. Volkova et al., EMNLP 2013.
• Overcoming language variation in sentiment analysis with social attention. Yang and Eisenstein. TACL, 2017.
• Personalized Machine Translation: Preserving Original Author Traits. Rabinovich et al, EACL 2017.

Large scale analyses

• A Kernel Independence Test for Geographical Language Variation. Nguyen and Eisenstein. To appear in Computational Linguistics.
• Aye or naw, whit dae ye hink? Scottish independence and linguistic identity on social media. Shoemark et al., EACL 2017.
• Demographic Dialectal Variation in Social Media: A Case Study of African-American English. Blodgett et al., EMNLP 2016.
• Toward a Description of African American Vernacular English Dialect Regions Using “Black Twitter”. Jones, American Speech 2015.

Language and Social Interaction

Social relationships

• Exploiting social network structure for person-to-person sentiment analysis. West et al., TACL 2014.
• Extracting social power relationships from natural language. Bramsen et al., ACL 2011.
• Gender and power: How gender and gender environment affect manifestations of power. Prabhakaran et al., EMNLP 2014.
• Phrases that signal workplace hierarchy. Gilbert, CSCW 2012.

Style shifting

• Audience-modulated variation in online social media. Pavalanathan and Eisenstein, American Speech, 2015.
• Centre stage: How social network position shapes linguistic coordination. Noble and Fernández, Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics, 2015
• Mark my words! Linguistic style accommodation in social media. Danescu-Niculescu-Mizil et al., WWW 2011.

Community dynamics

• Language use as a reflection of socialization in online communities. Nguyen and Rosé, Proceedings of the Workshop on Language in Social Media, 2011.
• Learning the lingo?: Gender, prestige and linguistic adaptation in review communities. Hemphill and Otterbacher, CSCW 2012.
• No country for old members: User lifecycle and linguistic change in online communities. Danescu-Niculescu-Mizil et al., WWW 2013.
• The language of online intercultural community formation. Cassell and Tversky, Journal of Computer-Mediated Communication, 2005.

Multilingual Communication

Automatic identification at the word level

• Labeling the languages of words in mixed-language documents using weakly supervised methods. King and Abney, NAACL 2013.
• Word level language identification in online multilingual communication. Nguyen and Doğruöz, EMNLP 2013.
• Overviews of the first and second shared task on language identification in code-switched data.

NLP tools for code-switched data

• Learning polylingual topic models from code-switched social media documents. Peng et al., ACL 2014.
• Part-of-speech tagging for English-Spanish code-switched text. Solorio and Liu, EMNLP 2008.
• POS tagging of English-Hindi code-mixed social media content. Vyas et al., EMNLP 2014.

Large scale analyses of multilingual communication in social media

• Audience and the use of minority languages on Twitter. Nguyen et al., ICWSM 2015.
• Global connectivity and multilinguals in the Twitter network. Hale, CHI 2014.
• Multilingual use of Twitter: Social networks at the language frontier. Eleta and Golbeck, Computers in Human Behavior, 2014.
• Sociolinguistic analysis of Twitter in multilingual societies. Suin et al., Hypertext 2014.
• Twitter users #codeswitch hashtags! #moltoimportante #wow.. Jurgens et al., Proceedings of the First Workshop on Computational Approaches to Code Switching, 2014.
• Understanding Language Preference for Expression of Opinion and Sentiment: What do Hindi-English Speakers do on Twitter? Rudra et al. EMNLP 2016

General resources on NLP code-switching research

• http://ritual.uh.edu/code-switching/ Bibliography and events overview
• Challenges of Computational Processing of Code-Switching, Çetinoğlu et al., Proceedings of the Second Workshop on Computational Approaches to Code Switching (2016). Overview of the impact of code-switching on NLP tasks.

Misc

• Ethics in NLP course/overview by Emily Bender.