CAREER: Towards a Data-driven Understanding of Online Sentiment

职业：以数据驱动的方式理解网络情绪

• 批准号: 2046590
• 负责人: Jeremy Blackburn
• 金额: $ 51.75万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2046590&HistoricalAwards=false
• 关键词: CAREER; Towards; Data; driven; Understanding

This project promotes the progress and advancement of scientific knowledge by exploring newmethods for understanding and modeling online sentiment. As the Web has become critical tosociety, impacting our personal lives as well as the world at large, a greater need to understandhow people interact. In particular, research into how to measure people’s opinion on varioustopics or types of content has failed to address the new ways and types of content used on theevolving social Web. This project addresses this lack of understanding by developing new toolsto help quantify online sentiment using large-scale, empirical data. In addition to these newtools, output from the project, including datasets and code artifacts will help other researchersadvance our understanding of social media.In this project, the investigator seeks to achieve four research objectives. The first is thecreation of a multi-platform social media dataset. In particular, the investigator will develop aseries of tools leveraging prior experience in large-scale data collection to perform continuousidentification and collection of multimedia data from emerging social media platforms. Next, theinvestigator will develop data-driven techniques to understand coded language used in socialmedia. These techniques will focus not just on textual content, e.g., slang words, but also codedvisual language, e.g., memes. The third objective is developing a new, explainable system forrating the sentiment of content. This method departs from existing approaches by treating theclassification task as a game between two pieces of content and learning a total ordering of thecontent devised from the Elo rating system used in chess and video games. Finally, theinvestigator will explore user and community level modeling of online sentiment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目通过探索理解和建模在线情感的新方法来促进科学知识的进步和进步。随着网络对社会变得至关重要，影响着我们的个人生活以及整个世界，更需要了解人们如何互动。特别是，关于如何衡量人们对各种观点或内容类型的看法的研究未能解决不断发展的社交网络上使用的新方式和内容类型。该项目通过开发新的工具来解决这种缺乏理解的问题，以帮助使用大规模的经验数据来量化在线情绪。除了这些新工具，项目的输出，包括数据集和代码工件将帮助其他研究人员推进我们对社交媒体的理解。在这个项目中，研究人员试图实现四个研究目标。第一个是创建一个多平台的社交媒体数据集。特别是，研究人员将利用之前在大规模数据收集方面的经验开发一系列工具，以执行来自新兴社交媒体平台的多媒体数据的持续识别和收集。接下来，研究人员将开发数据驱动技术来理解社交媒体中使用的编码语言。这些技术将不仅关注文本内容，例如，俚语，也包括编码的视觉语言，例如，模因第三个目标是开发一个新的，可解释的系统来评价内容的情感。这种方法不同于现有的方法，将分类任务视为两个内容之间的游戏，并学习从国际象棋和视频游戏中使用的Elo评级系统设计的内容的总排序。最后，研究者将探索用户和社区层面的在线情绪建模。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Non-Polar Opposites: Analyzing the Relationship Between Echo Chambers and Hostile Intergroup Interactions on Reddit

非极性对立：分析回声室与 Reddit 上敌对群体间互动之间的关系

• 发表时间: 2023
• 期刊: Proceedings of the AAAI International Conference on Web and Social Media
• 作者: Efstratiou, A.;Blackburn, J.;Caulfield, T.;Stringhini, G.;Zannettou, S.;De Cristofaro, E.
• 通讯作者: De Cristofaro, E.

A Multi-Platform Analysis of Political News Discussion and Sharing on Web Communities

• DOI: 10.1109/bigdata52589.2021.9671843
• 发表时间: 2021-03
• 期刊: 2021 IEEE International Conference on Big Data (Big Data)
• 作者: Yuping Wang;Savvas Zannettou;Jeremy Blackburn;B. Bradlyn;Emiliano De Cristofaro;G. Stringhini

"How over is it?" Understanding the Incel Community on YouTube

“怎么样了？”

• DOI: 10.1145/3479556
• 发表时间: 2021
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Papadamou, Kostantinos;Zannettou, Savvas;Blackburn, Jeremy;De Cristofaro, Emiliano;Stringhini, Gianluca;Sirivianos, Michael
• 通讯作者: Sirivianos, Michael

Lambretta: Learning to Rank for Twitter Soft Moderation

• DOI: 10.1109/sp46215.2023.10179392
• 发表时间: 2022-12
• 期刊: 2023 IEEE Symposium on Security and Privacy (SP)
• 作者: Pujan Paudel;Jeremy Blackburn;Emiliano De Cristofaro;Savvas Zannettou;G. Stringhini

TrollMagnifier: Detecting State-Sponsored Troll Accounts on Reddit

• DOI: 10.1109/sp46214.2022.9833706
• 发表时间: 2021-12
• 期刊: 2022 IEEE Symposium on Security and Privacy (SP)
• 作者: Mohammad Hammas Saeed;Shiza Ali;Jeremy Blackburn;Emiliano De Cristofaro;Savvas Zannettou;G. Stringhini