A BERT-based Deep Learning Approach for Reputation Analysis in Social Media

Mohammad Wali Ur Rahman, Sicong Shao, Pratik Satam, Salim Hariri, Chris Padilla, Zoe Taylor, Carlos Nevarez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Social media has become an essential part of the modern lifestyle, with its usage being highly prevalent. This has resulted in unprecedented amounts of data generated from users in social media, such as users' attitudes, opinions, interests, purchases, and activities across various aspects of their lives. Therefore, in a world of social media, where its power has shifted to users, actions taken by companies and public figures are subject to constantly being under scrutiny by influential global audiences. As a result, reputation management in social media has become essential as companies and public figures need to maintain their reputation to preserve their reputational capital. However, domain experts still face the challenge of lacking appropriate solutions to automate reliable online reputation analysis. To tackle this challenge, we proposed a novel reputation analysis approach based on the popular language model BERT (Bidirectional Encoder Representations from Transformers). The proposed approach was evaluated on the reputational polarity task using RepLab 2013 dataset. Compared to previous works, we achieved 5.8% improvement in accuracy, 26.9% improvement in balanced accuracy, and 21.8% improvement in terms of F-score.

Original languageEnglish (US)
Title of host publication2022 IEEE/ACS 19th International Conference on Computer Systems and Applications, AICCSA 2022 - Proceedings
PublisherIEEE Computer Society
ISBN (Electronic)9798350310085
DOIs
StatePublished - 2022
Event19th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2022 - Abu Dhabi, United Arab Emirates
Duration: Dec 5 2022Dec 7 2022

Publication series

NameProceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
Volume2022-December
ISSN (Print)2161-5322
ISSN (Electronic)2161-5330

Conference

Conference19th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2022
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period12/5/2212/7/22

Keywords

  • BERT
  • Reputation polarity
  • artificial intelligence
  • machine learning
  • natu-ral language processing
  • neural network
  • social media
  • transformers

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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