{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:04:09Z","timestamp":1760709849511},"reference-count":8,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Technol. Soc. Mag."],"published-print":{"date-parts":[[2019,3]]},"DOI":"10.1109\/mts.2019.2894472","type":"journal-article","created":{"date-parts":[[2019,3,11]],"date-time":"2019-03-11T18:35:40Z","timestamp":1552329340000},"page":"58-63","source":"Crossref","is-referenced-by-count":11,"title":["Twitter Data for Predicting Election Results: Insights from Emotion Classification"],"prefix":"10.1109","volume":"38","author":[{"given":"Satish M.","family":"Srinivasan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raghvinder S.","family":"Sangwan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Colin J.","family":"Neill","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianhai","family":"Zu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref4","article-title":"Emotional tweets","author":"mohammad","year":"0","journal-title":"Proc First Joint Conf Lexical and Computational Semantics"},{"key":"ref3","article-title":"Emotions evoked by common words and phrases: Using mechanical Turk to create an emotion lexicon","author":"mohammad","year":"0","journal-title":"Proceedings of the Workshop on Computational Approaches to Analysis and Generation of Emotion in Text 2010"},{"key":"ref6","author":"caldwell","year":"2016","journal-title":"5 major takeaways from the third and final 2016 presidential debate"},{"key":"ref5","year":"2016","journal-title":"United States presidential debates 2016"},{"key":"ref8","author":"contreras","year":"2016","journal-title":"Pence’s ‘Mexican thing’ remark draws ridicule from Latinos"},{"key":"ref7","author":"rogers","year":"2016","journal-title":"Trump won the third debate"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1037\/h0077714"},{"key":"ref1","author":"hasan","year":"2014","journal-title":"Emotex Detecting emotions in twitter messages"}],"container-title":["IEEE Technology and Society Magazine"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/44\/8664492\/08664560.pdf?arnumber=8664560","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:48:45Z","timestamp":1657745325000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8664560\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3]]},"references-count":8,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/mts.2019.2894472","relation":{},"ISSN":["0278-0097","1937-416X"],"issn-type":[{"value":"0278-0097","type":"print"},{"value":"1937-416X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3]]}}}