{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T16:08:00Z","timestamp":1770480480291,"version":"3.49.0"},"reference-count":23,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,9,15]]},"abstract":"<jats:p>Due to the COVID-19 pandemic, countries across the globe has enforced lockdown restrictions that influence the people\u2019s socio-economic lifecycle. The objective of this paper is to predict the communal emotion of people from different locations during the COVID-19 lockdown. The proposed work aims in developing a deep spatio-temporal analysis framework of geo-tagged tweets to predict the emotions of different topics based on location. An optimized Latent Dirichlet Allocation (LDA) approach is presented for finding the optimal hyper-parameters using grid search. A multi-class emotion classification model is then built via a Recurrent Neural Network (RNN) to predict emotions for each topic based on locations. The proposed work is experimented with the twitter streaming API dataset. The experimental results prove that the presented LDA model-using grid search along with the RNN model for emotion classification outperforms the other state of art methods with an improved accuracy of 94.6%.<\/jats:p>","DOI":"10.3233\/jifs-210544","type":"journal-article","created":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T10:59:02Z","timestamp":1627037942000},"page":"3251-3264","source":"Crossref","is-referenced-by-count":1,"title":["Deep spatio-temporal emotion analysis of\u00a0geo-tagged tweets for predicting location based communal emotion during COVID-19 Lock-down"],"prefix":"10.1177","volume":"41","author":[{"given":"M.","family":"Amsaprabhaa","sequence":"first","affiliation":[{"name":"Department of Computer Technology, Madras Institute of Technology (Anna University), Chennai, India"}]},{"given":"Y.","family":"Nancy Jane","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, Madras Institute of Technology (Anna University), Chennai, India"}]},{"given":"H.","family":"Khanna Nehemiah","sequence":"additional","affiliation":[{"name":"Ramanujan Computing Centre, Anna University, Chennai, India"}]}],"member":"179","reference":[{"issue":"4","key":"10.3233\/JIFS-210544_ref1","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1016\/j.ipm.2019.02.018","article-title":"Deep learning-based sentiment classification of evaluative text based on Multi-feature fusion","volume":"56","author":"Abdi","year":"2019","journal-title":"Information Processing & Management"},{"key":"10.3233\/JIFS-210544_ref2","doi-asserted-by":"publisher","DOI":"10.1109\/embc.2019.8857484"},{"issue":"4","key":"10.3233\/JIFS-210544_ref3","first-page":"304","article-title":"An LDA and Synonym Lexicon Based Approach to Product Feature Extraction from Online Consumer Product Reviews","volume":"14","author":"Ma","year":"2013","journal-title":"Journal of Electronic Commerce Research"},{"issue":"5","key":"10.3233\/JIFS-210544_ref5","doi-asserted-by":"publisher","first-page":"2770","DOI":"10.1109\/tgrs.2012.2219314","article-title":"Latent Dirichlet allocation for spatial analysis of satellite images","volume":"51","author":"Vaduva","year":"2013","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.3233\/JIFS-210544_ref6","doi-asserted-by":"publisher","DOI":"10.1109\/inista.2017.8001177"},{"key":"10.3233\/JIFS-210544_ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623638"},{"key":"10.3233\/JIFS-210544_ref9","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.future.2016.04.012","article-title":"Real-time event detection for online behavioral analysis of big social data","volume":"66","author":"Nguyen","year":"2017","journal-title":"Future Gener Comput Syst"},{"key":"10.3233\/JIFS-210544_ref12","doi-asserted-by":"publisher","DOI":"10.1109\/wi.2016.0091"},{"key":"10.3233\/JIFS-210544_ref14","doi-asserted-by":"publisher","DOI":"10.1109\/idap.2018.8620917"},{"key":"10.3233\/JIFS-210544_ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2207738"},{"issue":"6","key":"10.3233\/JIFS-210544_ref16","doi-asserted-by":"publisher","first-page":"102060","DOI":"10.1016\/j.ipm.2019.102060","article-title":"Fuzzy topic modeling approach for text mining over short text","volume":"56","author":"Rashid","year":"2019","journal-title":"Information Processing & Management"},{"key":"10.3233\/JIFS-210544_ref17","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3013933"},{"key":"10.3233\/JIFS-210544_ref18","doi-asserted-by":"publisher","DOI":"10.1109\/icaicta.2017.8090986"},{"key":"10.3233\/JIFS-210544_ref19","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1002\/asi.24245","article-title":"Public health and social media: A study of Zika virus-related posts on yahoo! 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