Investigation of Opinion Polarization in Online Communication: Towards an Integration of Explanation and Prediction

在线交流中意见两极分化的调查：走向解释与预测的整合

• 批准号: 22K20182
• 负责人: 呂 沢宇
• 金额: $ 1.83万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Research Activity Start-up
• 财政年份: 2022
• 资助国家: 日本
• 起止时间: 2022-08-31 至 2024-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-22K20182/
• 关键词: 計算社会科学; 分極化; ソーシャルメディア; ビッグデータ解析; 機械学習

This project attempts to explore the causal mechanism and construct a predictive model of opinion polarization in online communication. In the first year, two studies were processed.The first study employs large-scale social media data and advanced computational method to demonstrate how interparty hostility is associated with the partisan identity of both the message sender and the target in the interaction. The disparity in the extent of received offensive speech is argued to result from individuals' tendency to maintain their partisan identification by expressing hostility toward representative individuals of opposing partisan groups. The analysis also provides insights into how political polarization and inter-party hostility can mutually reinforce each other, thus contributing to the understanding of political polarization on social media.Second, based on the social survey in which respondents’ Twitter accounts were acquired, I have collected a wide range of social media data, including users’ profile information, published content, and network. The amalgamated dataset of social media data and survey data facilitates the development of a predictive model for opinion polarization in the future.

本研究试图探讨网络传播中意见极化的因果机制，并构建一个预测模型。在第一年，我们进行了两项研究，第一项研究使用了大规模的社交媒体数据和先进的计算方法，以证明在互动中，政党之间的敌意如何与信息发送者和目标的党派身份相关联。收到的攻击性言论的程度的差异被认为是由于个人的倾向，以保持他们的党派认同，表达对敌对党派团体的代表性个人的敌意。此外，通过分析，还可以认识到政治分化与政党对立之间的相互促进作用，从而有助于理解社会媒体上的政治分化。第二，根据以Twitter账号为对象的社会调查，收集了用户的个人资料、发布内容、网络等广泛的社会媒体数据。社交媒体数据和调查数据的合并数据集有助于开发未来意见两极分化的预测模型。

项目成果

Cross-Cutting Interaction, Out-Group Hostility, and Partisan Identity: Investigation of Affective Polarization on Social Media

跨领域互动、群体外敌意和党派认同：社交媒体上情感两极分化的调查

• 发表时间: 2022
• 作者: Masahiko SAMUKAWA;Hongwei LI;Hideaki MORIKAWA;Tsuyoshi OTANI;スズキトモ;藤原翔;大畑裕嗣;Zeyu Lyu
• 通讯作者: Zeyu Lyu

Computational Social Science Approach to Social Media Analysis

社交媒体分析的计算社会科学方法

• DOI: 10.24634/bunken.73.3_70
• 发表时间: 2023
• 期刊: The NHK Monthly Report on Broadcast Research
• 作者: 瀧川 裕貴;永吉 希久子;呂 沢宇;下窪 拓也;渡辺 誓司;中村 美子
• 通讯作者: 中村 美子