Detecting Inspiring Content on Social Media

被引:1
|
作者
Ignat, Oana [1 ]
Boureau, Y-Lan [2 ]
Yu, Jane A. [3 ]
Halevy, Alon [3 ]
机构
[1] Univ Michigan, Ann Arbor, MI 48109 USA
[2] Facebook AI, New York, NY USA
[3] Facebook AI, Menlo Pk, CA USA
关键词
inspiration; social media data; natural language processing; emotions; sentiment; INSPIRATION; COMMUNICATION;
D O I
10.1109/ACII52823.2021.9597431
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inspiration moves a person to see new possibilities and transforms the way they perceive their own potential. Inspiration has received little attention in psychology, and has not been researched before in the NLP community. To the best of our knowledge, this work is the first to study inspiration through machine learning methods. We aim to automatically detect inspiring content from social media data. To this end, we analyze social media posts to tease out what makes a post inspiring and what topics are inspiring. We release a dataset of 5,800 inspiring and 5,800 non-inspiring English-language public post unique ids collected from a dump of Reddit public posts made available by a third party and use linguistic heuristics to automatically detect which social media English-language posts are inspiring.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] Visualizing Social Media Content with SentenTree
    Hu, Mengdie
    Wongsuphasawat, Krist
    Stasko, John
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2017, 23 (01) : 621 - 630
  • [42] Popularity of Branded Content in Social Media
    Karpinska-Krakowiak, Malgorzata
    Modlinski, Artur
    JOURNAL OF COMPUTER INFORMATION SYSTEMS, 2020, 60 (04) : 309 - 315
  • [43] SOCIAL-CONTROL OF MEDIA CONTENT
    BEST, J
    JOURNAL OF POPULAR CULTURE, 1981, 14 (04): : 611 - 617
  • [44] Automatic content moderation on social media
    Karabulut, Dogus
    Ozcinar, Cagri
    Anbarjafari, Gholamreza
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (03) : 4439 - 4463
  • [45] Should Social Media Censor Content?
    Loria, Keith
    ECONTENT, 2014, 37 (09) : 6 - 8
  • [46] Quantifying the trustworthiness of social media content
    Sai T. Moturu
    Huan Liu
    Distributed and Parallel Databases, 2011, 29 : 239 - 260
  • [47] Evaluation of Content Credibility in Social Media
    Liu B.
    Li Y.
    Meng Q.
    Tang X.
    Cao J.
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2019, 56 (09): : 1939 - 1952
  • [48] The Dynamics of Content Popularity in Social Media
    Papadopoulos, Symeon
    Vakali, Athena
    Kompatsiaris, Ioannis
    INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 2010, 6 (01) : 20 - 37
  • [49] Detecting and filtering rumor in social media using news media event
    Kandasamy, Nithya
    Murugasamy, Krishnamoorthi
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2021, 33 (20):
  • [50] Characterizing Media Content and Effects of Organ Donation on a Social Media Platform: Content Analysis
    Jiang, Xiaoya
    Jiang, Wenshi
    Cai, Jiawei
    Su, Qingdong
    Zhou, Zhigang
    He, Lingnan
    Lai, Kaisheng
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2019, 21 (03)