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              <text>Sentiment Analysis On Covid-19 Related Social Distancing Across The Globe Using Twitter Data</text>
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              <text>Covid 19 pandemic has devastated the lives of several people across the globe. Social distancing is considered a major preventive measure to stop the spread of Covid 19. The practice of social distancing has caused a sense of loneliness and mental health problems in society. The aim of this study is to consider global tweet data with social distancing keywords for analyzing the sentiments behind them. Classification of tweets as positive or negative is carried out using Support Vector Machine and Logistic Regression.  The Electrochemical Society</text>
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              <text>Jyothsna R.; Rohini V.; Paulose J.</text>
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              <text>ECS Transactions, Vol-107, No. 1, pp. 3995-4001.</text>
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              <text>Institute of Physics</text>
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              <text>&lt;a href="https://doi.org/10.1149/10701.3995ecst" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1149/10701.3995ecst&lt;/a&gt;
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              <text>ISSN: 19386737; ISBN: 978-160768539-5</text>
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              <text>Jyothsna R., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Paulose J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India</text>
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