Exploit Social Relations in Sentiment Analysis of Social Media Content for Disaster Management Emergent Research Forum (ERF)

被引:0
作者
Shivarkar, Pratik [1 ]
Wei, Wei [1 ]
机构
[1] Univ Houston Clear Lake, Houston, TX 77058 USA
来源
AMCIS 2018 PROCEEDINGS | 2018年
关键词
Disaster Management; Social Media; Sentiment Analysis; Social Relation; Network Analysis; CRISIS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The world has witnessed the prevailing usage of social media for communication during disasters. Being able to monitor and predict public opinions on social media during disasters allows us to design more efficient and effective communication mechanisms during critical times. However, this potential is yet to be materialized due to difficulties in sentiment analysis of social media content. We propose to augment the effectiveness of such analysis by incorporating social relations in sentiment classification models. The proposed study extends previous work substantially by looking at a larger set of social relations and focusing on different communication goals at each stage of disaster management. In addition, we look at sentiments at both individual and community levels. The study can help formulate a better understanding of how opinions are formed and propagated during disasters, thus allow stakeholders to strategize for better communication.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Understanding social media data for disaster management
    Xiao, Yu
    Huang, Qunying
    Wu, Kai
    NATURAL HAZARDS, 2015, 79 (03) : 1663 - 1679
  • [32] Disaster Misinformation and Its Corrections on Social Media: Spatiotemporal Proximity, Social Network, and Sentiment Contagion
    Zhai, Wei
    Yu, Hang
    Song, Celine Yunya
    ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS, 2024, 114 (02) : 408 - 435
  • [33] MULDASA: Multifactor Lexical Sentiment Analysis of Social-Media Content in Nonstandard Arabic Social Media
    Alwakid, Ghadah
    Osman, Taha
    El Haj, Mahmoud
    Alanazi, Saad
    Humayun, Mamoona
    Sama, Najm Us
    APPLIED SCIENCES-BASEL, 2022, 12 (08):
  • [34] Understanding social media data for disaster management
    Yu Xiao
    Qunying Huang
    Kai Wu
    Natural Hazards, 2015, 79 : 1663 - 1679
  • [35] Deep Learning for Social Media Sentiment Analysis
    Fithriasari, Kartika
    Jannah, Saidah Zahrotul
    Reyhana, Zakya
    MATEMATIKA, 2020, 36 (02) : 99 - 111
  • [36] Sentiment Analysis on Social Media for Emotion Classification
    Tanna, Dilesh
    Dudhane, Manasi
    Sardar, Amrut
    Deshpande, Kiran
    Deshmukh, Neha
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS 2020), 2020, : 911 - 915
  • [37] A Study on Sentiment Analysis of Social Media Reviews
    Felciah, M. Lovelin Ponn
    Anbuselvi, R.
    2015 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INFORMATION, EMBEDDED AND COMMUNICATION SYSTEMS (ICIIECS), 2015,
  • [38] Supervised sentiment analysis in Czech social media
    Habernal, Ivan
    Ptacek, Tomas
    Steinberger, Josef
    INFORMATION PROCESSING & MANAGEMENT, 2014, 50 (05) : 693 - 707
  • [39] Sentiment Analysis in Social Media: A Comprehensive Bibliometric Analysis
    Tasente, Tanase
    Caratas, Maria Alina
    ADCOMUNICA-REVISTA CIENTIFICA DE ESTRATEGIAS TENDENCIAS E INNOVACION EN COMMUNICACION, 2024, (28): : 243 - 270
  • [40] Public Outlook on E-sports in China: A Content and Sentiment Analysis of Social Media
    Wang, Yifan
    Zheng, Xiaochuan
    Fan, Tianda
    2022 IEEE 23RD INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION FOR DATA SCIENCE (IRI 2022), 2022, : 270 - 277