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Time series sentiment analysis (SA) of relief operations using social media (SM) platform for efficient resource management

  • Published:2022-06 Issue: Volume:75 Page:102979
  • ISSN:2212-4209
  • Container-title:International Journal of Disaster Risk Reduction
  • language:en
  • Short-container-title:International Journal of Disaster Risk Reduction

Author:

Bhullar GurmanORCID,Khullar AseemORCID,Kumar ApoorvaORCID,Sharma AnirudhORCID,Pannu H.S.,Malhi Avleen

Publisher

Elsevier BV

Subject

Geology,Safety Research,Geotechnical Engineering and Engineering Geology,Building and Construction

Reference46 articles.

1. Analyzing and preprocessing the twitter data for opinion mining;Anand,2018

2. Mining twitter to inform disaster response;Ashktorab,2014

3. The role of pre-processing in twitter sentiment analysis;Bao,2014

4. Extracting resource needs and availabilities from microblogs for aiding post-disaster relief operations;Basu;IEEE Trans. Comput. Soc. Syst.,2019

5. Extracting resource needs and availabilities from microblogs for aiding post-disaster relief operations;Basu;IEEE Trans. Comput. Soc. Syst.,2019

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1. A systematic review of trustworthy artificial intelligence applications in natural disasters;Computers and Electrical Engineering;2024-09

2. Twitter analysis in emergency management: recent research and trends;Social Network Analysis and Mining;2024-08-07

3. Convergence of artificial intelligence with social media: A bibliometric & qualitative analysis;Telematics and Informatics Reports;2024-06

4. Social Media Sentiment Analysis Using Twitter Dataset;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

5. Sentiment time series clustering of Danmu videos based on BERT fine-tuning and SBD-K-shape;The Electronic Library;2024-04-22
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