| Challenge: | Social media is a rich source of assertions about personal traits, but identifying personal traits from implicit assertions is difficult because of the users’ highly varied vocabulary and expressions. |
| Approach: | They propose to build a large-scale annotated resource for user profiling for over 300k Reddit users across five attributes: profession, hobby, family status, age, and gender. |
| Outcome: | The proposed resource is the first annotated language resource about Reddit users at large scale. |
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| Challenge: | Social media platforms such as Reddit are vulnerable to misinformation and disinformation. |
| Approach: | They propose a method to automatically derive (noisy) supervision for retrieval of trustworthy evidence relevant to a given claim made on social media. |
| Outcome: | The proposed method outperforms baseline models in the retrieval task performed by medical doctors. |
CHARM: Inferring Personal Attributes from Conversations (2020.emnlp-main)
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| Challenge: | Personal Knowledge Bases (PKBs) capture individual user traits for customizing downstream applications like chatbots or recommenders. |
| Approach: | They propose a method that leverages keyword extraction and document retrieval to predict attribute values that were never seen during training. |
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Dreaddit: A Reddit Dataset for Stress Analysis in Social Media (D19-62)
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| Challenge: | Existing computational studies on stress only focus on domains such as speech or Twitter . a corpus of social media text is used to identify stress . |
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Leveraging Similar Users for Personalized Language Modeling with Limited Data (2022.acl-long)
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| Challenge: | Recent work suggests that personalized models are more accurate for individual users than one-size-fits-all solutions. |
| Approach: | They propose a model trained on users that are similar to a new user to find similarity between new and existing users. |
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SOBR: A Corpus for Stylometry, Obfuscation, and Bias on Reddit (2024.lrec-main)
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| Challenge: | Existing corpora are limited in scope and can be used to collect data on author attributes. |
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RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models (2021.acl-long)
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| Challenge: | Recent work has focused on measuring and mitigating bias in pretrained language models. |
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RU-ADEPT: Russian Anonymized Dataset with Eight Personality Traits (2022.lrec-1)
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C. Anton Rytting, Valerie Novak, James R. Hull, Victor M. Frank, Paul Rodrigues, Jarrett G. W. Lee, Laurel Miller-Sims
| Challenge: | Social media has provided a platform for many individuals to express themselves naturally and publicly, but most of the work in this area has focused on English and other Western European languages. |
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#HowYouTagTweets: Learning User Hashtagging Preferences via Personalized Topic Attention (2021.emnlp-main)
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| Challenge: | Existing methods based on latent topics cannot capture user interests and thus can't be used to predict how likely a user will post with a hashtag. |
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Beyond Discrete Personas: Personality Modeling Through Journal Intensive Conversations (2025.coling-main)
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| Challenge: | Existing LLMs rely on static, predefined personas to capture dynamic and evolving nature of human personalities. |
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The Engage Corpus: A Social Media Dataset for Text-Based Recommender Systems (2022.lrec-1)
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| Challenge: | Existing studies have examined the impact of recommendation algorithms on how users discover and join online groups, but there are few standardized datasets for generating such models. |
| Approach: | They propose to use Reddit to build a dataset that can be used to build models of user engagement with online groups. |
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