| Challenge: | Several studies have applied computational approaches to the understanding and modeling of human behavior at scale and in real time. |
| Approach: | They propose a sentence embedding framework tailored to recognize the semantics of human activities and perform automatic clustering of these activities. |
| Outcome: | The proposed framework can make predictions based on the text of user-generated content and self-description. |
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| Challenge: | Recent studies have shown that user-level features can carry more task-related information than the text itself. |
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| Challenge: | Recent studies have shown that textual information of user posts and user behaviors are useful for predicting the personality of social media users. |
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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 work on re-entry prediction ignores conversation thread patterns and repeated engagement of target users. |
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Kyuyong Shin, Hanock Kwak, Wonjae Kim, Jisu Jeong, Seungjae Jung, Kyungmin Kim, Jung-Woo Ha, Sang-Woo Lee
| Challenge: | Recent studies have proposed unified user modeling frameworks that leverage user behavior data from various applications. |
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Creation and evaluation of timelines for longitudinal user posts (2023.eacl-main)
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| Challenge: | Existing methods for segmenting user posts into timelines improve quality and cost of manual annotation. |
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