<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="4.3.0" xmlns="http://www.crossref.org/doi_resources_schema/4.3.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/doi_resources_schema/4.3.0 http://www.crossref.org/schema/deposit/doi_resources4.3.0.xsd">
<head>
<doi_batch_id>a7332994-da5e-4dc5-a400-446bd97895eb</doi_batch_id>
<depositor>
<name>beie</name>
<email_address>director@blueeyesintelligence.org</email_address>
</depositor>
</head>
<body>
<doi_citations>
<doi>10.35940/ijrte.E5260.019521</doi>
<citation_list><citation key="ref0"><unstructured_citation>Coronavirus Disease, https://en.wikipedia.org/wiki/Coronavirus_disease, 2020</unstructured_citation></citation><citation key="ref1"><unstructured_citation>Worldometers.info, https://www.worldometers.info/coronavirus/, 2020</unstructured_citation></citation><citation key="ref2"><unstructured_citation>World Health Organization (WHO), Who director-general's opening remarks at the media briefing on covid-19 - 11 march 2020,</unstructured_citation></citation><citation key="ref3"><unstructured_citation>https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-atthe-media-briefing-on-covid-19---11-march-2020.</unstructured_citation></citation><citation key="ref4"><doi>10.1109/ICBDA.2016.7509810</doi><unstructured_citation>Chen, J., Jiang, Q., Wang, Y., Tang, J.: Study of data analysis model based on big data technology. In: IEEE International Conference on Big Data Analysis (ICBDA), pp. 1-6. IEEE, (March 2016)</unstructured_citation></citation><citation key="ref5"><doi>10.1177/2053951719843310</doi><unstructured_citation>Torabi Asr, F., &amp; Taboada, M.: Big Data and quality data for fake news and misinformation detection. Big Data and Society,6(1), 1-14, (2019).</unstructured_citation></citation><citation key="ref6"><unstructured_citation>World Health Organization (WHO), A Coordinated Global Research Roadmap, https://www.who.int/publications/m/item/a-coordinated-global-research-roadmap (2020)</unstructured_citation></citation><citation key="ref7"><doi>10.1109/BigData47090.2019.9005561</doi><unstructured_citation>Tran T., Rad. P., et. al.: Misinformation Harms During Crises: When The Human And Machine Loops Interact, In: 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, 2019, pp. 4644-4646, (2019).</unstructured_citation></citation><citation key="ref8"><doi>10.1109/ICHI.2017.58</doi><unstructured_citation>Ghenai A., Mejova Y.: Catching Zika fever: application of crowdsourcing and machine learning for tracking health misinformation on Twitter, (2017).</unstructured_citation></citation><citation key="ref9"><doi>10.2196/18444</doi><unstructured_citation>Cuan-Baltazar, J. Y., Muñoz-Perez, M. J., Robledo-Vega, C., Pérez-Zepeda, M. F., &amp; Soto-Vega, E.: Misinformation of COVID-19 on the internet: infodemiology study. JMIR Public Health Surveill,6(2), e18444, (2020).</unstructured_citation></citation><citation key="ref10"><doi>10.3961/jpmph.20.094</doi><unstructured_citation>Tasnim S. C., Hossain M., Mazumder H.: Impact of Rumors and Misinformation on COVID-19 in Social Media, In: Journal of Preventive Medicine and Public Health vol.53, pp.171-174, (2020)</unstructured_citation></citation><citation key="ref11"><unstructured_citation>Neilson R. K., Fletcher R., et.al.: Navigating the 'infodemic': how people in six countries access and rate news and information about coronavirus, In: Misinformation, science, and media. The Reuters Institute for the Study of Journalism and University of Oxford, pp. 2020-04, (2020)</unstructured_citation></citation><citation key="ref12"><unstructured_citation>Outlook India, Tune in--Community radio stations aid fight against coronavirus with local touch, https://www.outlookindia.com/newsscroll/tune-incommunity-radiostations-aid-fight-against-coronavirus-with-local-touch/1815082.</unstructured_citation></citation><citation key="ref13"><doi>10.1017/S0008423920000396</doi><unstructured_citation>Motta, M., Stecula, D., &amp; Farhart, C.: How Right-Leaning Media Coverage of COVID19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic in the U.S. Canadian Journal of Political Science, vol. 53, no. 2, 335-342, (2020)</unstructured_citation></citation><citation key="ref14"><unstructured_citation>Shapiro J. N. and Oledan J.: ESOC COVID-19 Disinformation Tracking Report. In: Empirical Studies of Conflict. https://esoc.princeton.edu/publications/esoc-covid-19disinformation-tracking-report, (2020)</unstructured_citation></citation><citation key="ref15"><doi>10.1109/IV.2014.72</doi><unstructured_citation>Burch, M., Lohmann, S., Beck, F., Rodriguez, N., Di Silvestro, L., Weiskopf, D.: Radcloud: visualizing multiple texts with merged word clouds. In: 2014 18th International Conference on Information Visualisation (IV), pp. 108-113. IEEE, (2014)</unstructured_citation></citation><citation key="ref16"><doi>10.1109/HICSS.2014.231</doi><unstructured_citation>Heimerl, F., Lohmann, S., Lange, S., Ertl, T.: Word cloud explorer: text analytics based on word clouds. In: 2014 47th Hawaii International Conference on System Sciences (HICSS), pp. 1833-1842. IEEE (2014)</unstructured_citation></citation><citation key="ref17"><doi>10.35940/ijrte.C6503.098319</doi><unstructured_citation>Katre. P.: NLP Based Text Analytics and Visualization of Political Speeches. In: International Journal of Recent Technology and Engineering (IJRTE), vol. 8(3), pp. 8574-8579, (2019).</unstructured_citation></citation><citation key="ref18"><doi>10.1109/IACC48062.2019.8971605</doi><unstructured_citation>Kate. P.: Text Mining and Comparative Visual Analytics on Large Collection of Speeches to Trace Socio-Political Issues. In: 2019 IEEE 9th International Conference on Advanced Computing (IACC), pp. 108-114, IEEE, (2019)</unstructured_citation></citation></citation_list>
</doi_citations>
</body>
</doi_batch>
