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Comput."],"published-print":{"date-parts":[[2020,9,30]]},"abstract":"<jats:p>Humans have a natural tendency to form social groups, and individual behaviours are thought to be strongly influenced by a salient sense of belonging to one or more such groups. It can be expected, therefore, that there will be behaviours that are specific to the group(s) to which a person currently feels they are interacting with and that some of these behaviours will manifest in topics and patterns of linguistic style associated with those groups. Here we explore this idea by attempting to identify group specific patterns of language usage in social media data from Twitter and Reddit. Topic models are used to infer patterns of language usage and group structures are either provided with the data (Reddit) inferred from the follower network (Twitter). We apply a Bayesian graphical model to infer community-topic associations, finding that substantially more coherent associations can often be identified than with a naive probability-based approach. Strong associations are found between groups and topics with both approaches, indicating that the methods used to (independently) identify groups and topics represent real underlying patterns of social communication and promising fruitful investigation of human social behaviour using these or similar techniques.<\/jats:p>","DOI":"10.1145\/3377870","type":"journal-article","created":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T04:35:08Z","timestamp":1590986108000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Community Topic Usage in Online Social Media"],"prefix":"10.1145","volume":"3","author":[{"given":"Ian D.","family":"Wood","sequence":"first","affiliation":[{"name":"Macquarie Univeristy, Balaclava Road, North Ryde, NSW, Australia"}]},{"given":"John","family":"Glover","sequence":"additional","affiliation":[{"name":"AYLIEN LTD., Harmony Court, Harmony Row, Dublin, Ireland"}]},{"given":"Paul","family":"Buitelaar","sequence":"additional","affiliation":[{"name":"National University of Ireland Galway, University Road, Galway, Ireland"}]}],"member":"320","published-online":{"date-parts":[[2020,5,31]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Xing","author":"Airoldi Edoardo M.","year":"2009","unstructured":"Edoardo M. 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MEI: Mutual enhanced infinite generative model for simultaneous community and topic detection. In Discovery Science . Springer , 91--106. Dongsheng Duan, Yuhua Li, Ruixuan Li, Zhengding Lu, and Aiming Wen. 2011. MEI: Mutual enhanced infinite generative model for simultaneous community and topic detection. In Discovery Science. Springer, 91--106."},{"key":"e_1_2_1_7_1","first-page":"733","article-title":"Posterior predictive assessment of model fitness via realized discrepancies","volume":"6","author":"Gelman Andrew","year":"1996","unstructured":"Andrew Gelman , Xiao-Li Meng , and Hal Stern . 1996 . Posterior predictive assessment of model fitness via realized discrepancies . Stat. Sin. 6 , 4 (1996), 733 -- 760 . Andrew Gelman, Xiao-Li Meng, and Hal Stern. 1996. Posterior predictive assessment of model fitness via realized discrepancies. Stat. Sin. 6, 4 (1996), 733--760.","journal-title":"Stat. 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Topic modeling on health journals with regularized variational inference. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1221839110"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0307752101"},{"key":"e_1_2_1_12_1","volume-title":"Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. Blog post","author":"Himelboim Itai","year":"2014","unstructured":"Itai Himelboim . 2014. Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. Blog post . Pew Research Center\u2019s Internet 8 American Life Project. http:\/\/www.pewinternet.org\/ 2014 \/02\/20\/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters\/. Itai Himelboim. 2014. Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. Blog post. Pew Research Center\u2019s Internet 8 American Life Project. http:\/\/www.pewinternet.org\/2014\/02\/20\/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters\/."},{"volume-title":"Social Networks that Matter: Twitter under the Microscope. SSRN Scholarly Paper ID 1313405. Social Science Research Network","author":"Huberman Bernardo A.","key":"e_1_2_1_13_1","unstructured":"Bernardo A. Huberman , Daniel M. Romero , and Fang Wu. 2008. Social Networks that Matter: Twitter under the Microscope. SSRN Scholarly Paper ID 1313405. Social Science Research Network , Rochester, NY . Bernardo A. Huberman, Daniel M. Romero, and Fang Wu. 2008. Social Networks that Matter: Twitter under the Microscope. SSRN Scholarly Paper ID 1313405. Social Science Research Network, Rochester, NY."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1348549.1348556"},{"volume-title":"Advances in Neural Information Processing Systems 25","author":"Larochelle Hugo","key":"e_1_2_1_15_1","unstructured":"Hugo Larochelle and Stanislas Lauly . 2012. A neural autoregressive topic model . In Advances in Neural Information Processing Systems 25 , F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger (Eds.). Curran Associates, Inc. , 2708--2716. Hugo Larochelle and Stanislas Lauly. 2012. A neural autoregressive topic model. In Advances in Neural Information Processing Systems 25, F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger (Eds.). Curran Associates, Inc., 2708--2716."},{"key":"e_1_2_1_16_1","first-page":"237","article-title":"Adding community and dynamic to topic models","volume":"6","author":"Li Daifeng","year":"2012","unstructured":"Daifeng Li , Ying Ding , Xin Shuai , Johan Bollen , Jie Tang , Shanshan Chen , Jiayi Zhu , and Guilherme Rocha . 2012 . Adding community and dynamic to topic models . J. Inf. 6 , 2 (2012), 237 -- 253 . Daifeng Li, Ying Ding, Xin Shuai, Johan Bollen, Jie Tang, Shanshan Chen, Jiayi Zhu, and Guilherme Rocha. 2012. Adding community and dynamic to topic models. J. Inf. 6, 2 (2012), 237--253.","journal-title":"J. Inf."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1871437.1871673"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553460"},{"volume-title":"Proceedings of the International AAAI Conference on Web and Social Media (ICWSM\u201911)","author":"Michael","key":"e_1_2_1_19_1","unstructured":"Michael J. Paul and Mark Dredze. 2011. You are what you tweet: Analyzing Twitter for public health . In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM\u201911) . Michael J. Paul and Mark Dredze. 2011. You are what you tweet: Analyzing Twitter for public health. In Proceedings of the International AAAI Conference on Web and Social Media (ICWSM\u201911)."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.5555\/1036843.1036902"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2684822.2685324"},{"key":"e_1_2_1_22_1","doi-asserted-by":"crossref","unstructured":"G. Sammut E. Andreouli G. Gaskell and J. Valsiner. 2015. Social representations: A revolutionary paradigm? In The Cambridge Handbook of Social Representations G. Sammut E. Andreouli G. Gaskell and J. Valsiner (Eds.). Cambridge University Press Cambridge UK 3--11.  G. Sammut E. Andreouli G. Gaskell and J. Valsiner. 2015. Social representations: A revolutionary paradigm? 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