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Social scientists increasingly use demographically stratified social media data to study the attitudes, beliefs, and behavior of the general public.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Homophily and latent attribute inference: Inferring latent attributes of twitter users from neighbors
Faiyaz Al Zamal, Wendy Liu, and Derek Ruths. 2012 · 2012
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Language independent gender classification on twitter
Jalal S Alowibdi, Ugo A Buy, and Philip Yu. 2013 · 2013
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Exploring demographic language variations to improve multilingual sentiment analysis in social media
Svitlana Volkova, Theresa Wilson, and David Yarowsky. 2013 · 2013
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Estimating county health statistics with twitter
Aron Culotta. 2014 · 2014
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The eyes of the beholder: Gender prediction using images posted in online social networks
Quanzeng You, Sumit Bhatia, Tong Sun, and Jiebo Luo. 2014 · 2014
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Birds of the same feather tweet together: Bayesian ideal point estimation using twitter data
Pablo Barberá. 2015 · 2015
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Gender differences in the climate change communication on twitter
Kim Holmberg and Iina Hellsten. 2015 · 2015
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Demographic factors improve classification performance
Dirk Hovy. 2015 · 2015
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Age and gender classification using convolutional neural networks
Gil Levi and Tal Hassner. 2015 · 2015
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Who tweets in italian? demographic characteristics of twitter users
Righi Alessandra, Mauro M Gentile, and Domenico M Bianco. 2019 · 2017
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Human centered nlp with user-factor adaptation
Veronica Lynn, Youngseo Son, Vivek Kulkarni, Niranjan Balasubramanian, and H Andrew Schwartz. 2017 · 2017
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Beyond binary labels: Political ideology prediction of twitter users
Daniel Preoţiuc-Pietro, Ye Liu, Daniel Hopkins, and Lyle Ungar. 2017 · 2017
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Towards robust and privacy-preserving text representations
Yitong Li, Timothy Baldwin, and Trevor Cohn. 2018 · 2018
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User-level race and ethnicity predictors from twitter text
Daniel Preoţiuc-Pietro and Lyle Ungar. 2018 · 2018
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Twitter as data
Zachary C Steinert-Threlkeld. 2018 · 2018
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Twitter makes it worse: Political journalists, gendered echo chambers, and the amplification of gender bias
Nikki Usher, Jesse Holcomb, and Justin Littman. 2018 · 2018
Cited alongside, same era.
Predicting individual-level income from facebook profiles
Twitter-demographer: A flow-based tool to enrich twitter data
Federico Bianchi, Vincenzo Cutrona, and Dirk Hovy. 2022 · 2022
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2022 · 2022
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Jobs, hobbies top the list of things u.s. adults put in their twitter profiles; references to politics relatively rare, by regina widjaya
Pew. 2022 · 2022
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Monitoring depression trends on twitter during the covid-19 pandemic: observational study
Yipeng Zhang, Hanjia Lyu, Yubao Liu, Xiyang Zhang, Yu Wang, and Jiebo Luo. 2021 · 2022
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It’s all in the name: A character-based approach to infer religion
Rochana Chaturvedi and Sugat Chaturvedi. 2023 · 2023
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Sandra C Matz, Jochen I Menges, David J Stillwell, and H Andrew Schwartz. 2019 · 2019
Cited alongside, same era.
Estimating geographic subjective well-being from twitter: A comparison of dictionary and data-driven language methods
Kokil Jaidka, Salvatore Giorgi, H Andrew Schwartz, Margaret L Kern, Lyle H Ungar, and Johannes C Eichstaedt. 2020 · 2020
Cited alongside, same era.
Xlm-t: Multilingual language models in twitter for sentiment analysis and beyond
Francesco Barbieri, Luis Espinosa Anke, and Jose Camacho-Collados. 2021 · 2021
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Individuals with depression express more distorted thinking on social media
Krishna C Bathina, Marijn Ten Thij, Lorenzo Lorenzo-Luaces, Lauren A Rutter, and Johan Bollen. 2021 · 2021
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Demographics and topics impact on the co-spread of covid-19 misinformation and fact-checks on twitter
Grégoire Burel, Tracie Farrell, and Harith Alani. 2021 · 2021
Cited alongside, same era.
The importance of modeling social factors of language: Theory and practice
Dirk Hovy and Diyi Yang. 2021 · 2021
Cited alongside, same era.
Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program
Jennifer Allen, Cameron Martel, and David G Rand. 2022 · 2022
Cited alongside, same era.
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The effect of social media on elections: Evidence from the united states
Thomas Fujiwara, Karsten Müller, and Carlo Schwarz. 2023 · 2023
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Name-based demographic inference and the unequal distribution of misrecognition
Jeffrey W Lockhart, Molly M King, and Christin Munsch. 2023 · 2023
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Towards human-level text coding with llms: The case of fatherhood roles in public policy documents
Lorenzo Lupo, Oscar Magnusson, Dirk Hovy, Elin Naurin, and Lena Wängnerud. 2023 · 2023
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Leveraging label variation in large language models for zero-shot text classification
Flor Miriam Plaza-del Arco, Debora Nozza, and Dirk Hovy. 2023 · 2023
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Social media: Twitter users in italy
Statista. 2023 · 2023
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Demographic inference and representative population estimates from multilingual social media data
Zijian Wang, Scott Hale, David Ifeoluwa Adelani, Przemyslaw Grabowicz, Timo Hartman, Fabian Flöck, and David Jurgens. 2019 · 2067
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