A Sentimental and Semantical Analysis on Facebook Comments to Detect Latent Patterns

Mahdi Naser Moghadasi, Zohreh Safari, Yu Zhuang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Social media posts and their comments are rich in variation of subjects and an interesting pool for opinion mining. Individuals engage in social communications on Facebook through three behaviors: like, share and comment on a Facebook post. Responses to comments are grouped under the respective comment as a conversation thread. Conversation threads become interesting when users have conflicting views with the article posted, or with the opinion of another user. Our research goal is to answer questions such as why some posts in Facebook receive more attention than others? Are conversation threads following a similar pattern between subjects like sport and politics? Is there any harmony between conversation threads of different subjects? We investigated how individuals react to different conversation subjects in the Facebook through a comprehensive analysis. Our aim is to discover semantic and sentimental patterns in conversation threads categories. Finally, we employed Natural Language Processing techniques such as semantic and sentimental analysis and statistical methods like average response time (ART) and average comment length (ACL) of a post and observed that there are interesting patterns exists among different conversation threads.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
EditorsXintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4665-4671
Number of pages7
ISBN (Electronic)9781728162515
DOIs
StatePublished - Dec 10 2020
Event8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States
Duration: Dec 10 2020Dec 13 2020

Publication series

NameProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

Conference

Conference8th IEEE International Conference on Big Data, Big Data 2020
CountryUnited States
CityVirtual, Atlanta
Period12/10/2012/13/20

Keywords

  • Data Mining
  • Semantic Analysis
  • Social Analysis

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