Measuring the Effect of Influential Messages on Varying Personas (2023.acl-short)
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| Challenge: | a new task estimates the response a persona might have upon seeing a news message . a first benchmark dataset is used to evaluate the performance of the proposed task . |
| Approach: | They propose a task to estimate the response a persona might have upon seeing a news message. |
| Outcome: | The proposed task estimates the response a persona might have upon seeing a news message. |
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| Challenge: | Existing methods to predict sentiments on social media are limited and do not consider reciprocal influences among social media users. |
| Approach: | They propose a multi-perspective role-playing framework to simulate human response processes to extract sentiment-related features from social media messages. |
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iNews: A Multimodal Dataset for Modeling Personalized Affective Responses to News (2025.acl-long)
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| Challenge: | Current approaches to modeling individual behavior ignore individual differences in how people interpret and react to identical stimuli. |
| Approach: | They propose a large-scale dataset specifically designed to facilitate the modeling of personalized affective responses to news content. |
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Distribution of Emotional Reactions to News Articles in Twitter (L18-1)
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| Challenge: | Social networks have created datasets of opinions of users that focus on the writers' perspective, which does not consider the source that provokes those opinions. |
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Guiding Variational Response Generator to Exploit Persona (2020.acl-main)
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Bowen Wu, MengYuan Li, Zongsheng Wang, Yifu Chen, Derek F. Wong, Qihang Feng, Junhong Huang, Baoxun Wang
| Challenge: | Neural Response Generators (NRGs) use persona information of users to perform personalized conversations . current studies focus on incorporating explicit meta-data of user profiles or character descriptions to generate persona-aware responses. |
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Hierarchical Modeling for User Personality Prediction: The Role of Message-Level Attention (2020.acl-main)
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| Challenge: | Language processing is increasingly finding use as a supplement for questionnaires to assess psychological attributes of consenting individuals, but most approaches neglect to consider whether all documents of an individual are equally informative. |
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An Individualized News Affective Response Dataset (2024.acl-srw)
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| Challenge: | a new dataset captures subjective affective responses to news headlines . current methods to assess emotion detection ignore subjective differences in groups and individuals . |
| Approach: | They propose a large-scale dataset capturing subjective affective responses to news headlines . the dataset includes Facebook post screenshots from popular UK media outlets . |
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Persona-E²: A Human-Grounded Dataset for Personality-Shaped Emotional Responses to Textual Events (2026.acl-long)
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Yuqin Yang, Haowu Zhou, Haoran Tu, Zhiwen Hui, Shiqi Yan, HaoYang Li, Dong She, Xianrong Yao, Yang Gao, Zhanpeng Jin
| Challenge: | A critical bottleneck is the lack of ground-truth human data to link personality traits to emotional shifts. |
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NewsMTSC: A Dataset for (Multi-)Target-dependent Sentiment Classification in Political News Articles (2021.eacl-main)
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| Challenge: | Previous work on target-dependent sentiment classification (TSC) has focused on reviews, social media, and other domains where authors tend to express their opinions explicitly. |
| Approach: | They propose a high-quality dataset for TSC on news articles with key differences compared to established datasets. |
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We Can Detect Your Bias: Predicting the Political Ideology of News Articles (2020.emnlp-main)
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| Challenge: | a new study examines the role of media in predicting political ideology or bias in news articles . systematic exposure to bias in the news can foster intolerance and ideological segregation . |
| Approach: | They propose an adversarial media adaptation and a specially adapted triplet loss for predicting political ideology in news articles. |
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PopALM: Popularity-Aligned Language Models for Social Media Trendy Response Prediction (2024.lrec-main)
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| Challenge: | Recent work focuses on generic human responses without considering popularity factors in the social contexts. |
| Approach: | They propose Popularity-Aligned Language Models to distinguish responses liked by a larger audience through reinforcement learning. |
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