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Going beyond accuracy: estimating homophily in social networks using predictions

, , , , and . (2020)cite arxiv:2001.11171Comment: 19 pages, 4 figures, 2 tables.

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Going beyond accuracy: estimating homophily in social networks using predictions, , , , and . (2020)cite arxiv:2001.11171Comment: 19 pages, 4 figures, 2 tables.Stylistic Features Usage: Similarities and Differences Using Multiple Social Networks., , and . SocInfo, volume 11864 of Lecture Notes in Computer Science, page 309-318. Springer, (2019)Gender and Racial Diversity in Commercial Brands' Advertising Images on Social Media., and . SocInfo, volume 11864 of Lecture Notes in Computer Science, page 79-94. Springer, (2019)Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus., , and . ICWSM, page 1409-1413. AAAI Press, (2022)The Challenges of Creating Engaging Content: Results from a Focus Group Study of a Popular News Media Organization., , and . CHI Extended Abstracts, ACM, (2019)Characterizing Spontaneous Ideation Contest on Social Media: Case Study on the Name Change of Facebook to Meta., , , and . IEEE Big Data, page 776-783. IEEE, (2022)Confusion Prediction from Eye-Tracking Data: Experiments with Machine Learning., , , , , and . ICIST, page 5:1-5:9. ACM, (2019)Tanbih: Get To Know What You Are Reading., , , , , , , , , and 3 other author(s). EMNLP/IJCNLP (3), page 223-228. Association for Computational Linguistics, (2019)What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context., , , , , , , and . ACL, page 3364-3374. Association for Computational Linguistics, (2020)Viewed by too many or viewed too little: Using information dissemination for audience segmentation., , , , and . ASIST, volume 54 of Proc. Assoc. Inf. Sci. Technol., page 189-196. Wiley, (2017)