Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak

Author:

Mittal Ruchi,Mittal AmitORCID,Aggarwal Ishan

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems

Reference90 articles.

1. Achrekar H, Gandhe A, Lazarus R, Yu SH, & Liu B (2011). Predicting flu trends using Twitter data. In: 2011 IEEE conference on computer communications workshops (INFOCOM WKSHPS). IEEE. pp. 702–707

2. Agarwal A, Singh R, Toshniwal D (2018) Geospatial sentiment analysis using twitter data for UK-EU referendum. J Inf Optim Sci 39(1):303–317

3. Agarwal A, Xie B, Vovsha I, Rambow O, & Passonneau RJ (2011). Sentiment analysis of twitter data. In Proceedings of the workshop on language in social media (LSM 2011). pp. 30–38

4. Ahmed W, Bath PA, Sbaffi L, Demartini G (2019) Novel insights into views towards H1N1 during the 2009 pandemic: a thematic analysis of Twitter data. Health Info Libr J 36(1):60–72

5. Ahmed W, Demaerini G, & Bath PA (2017) Topics discussed on twitter at the beginning of the 2014 Ebola epidemic in United States. In: Conference 2017 proceedings

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