اتجاهات مستخدمي مواقع التواصل الاجتماعي نحو جائحة کورونا (کوفيد -19): تحليل من المستوى الثاني لدراسات مدخل معالجة اللغة الطبيعية

Aguilar, N. , Romero-García, L. , Martínez-G., Sánchez, E. , Jorge, A. (2020). Dataset on dynamics of Coronavirus on Twitter. Data in Brief. 30. Doi:10.1016/j.dib.2020.105684.

Alhajji, M., Al Khalifah, A., Aljubran, M., Alkhalifah, M. (2020).Sentiment Analysis of Tweets in Saudi Arabia Regarding Governmental Preventive Measures to Contain COVID-19. Preprints .2020040031 (doi: 10.20944/preprints202004.0031.v1).

Al-Rawi, A., Siddiqi, M., Morgan, R. , Vandan, N. , Smith, J. , Wenham, C. (2020). COVID-19 and the Gendered Use of Emojis on Twitter: Infodemiology Study. Journal of Medical Internet Research. 22(11). DOI: 10.2196/21646.

Al hazmi,H.&Alharbi, M.(2020).emotion analysis of Arabic tweets during Covid 19 pandemic in Saudi Arabia. (IJACSA) International Journal of Advanced Computer Science and Applications. (11)10.619-625-https://thesai.org/Downloads/Volume11No10/Paper_77-Emotion_Analysis_of_Arabic_Tweets_during_COVID_19.pdf

Ani, N. , Anikwenze, C. & Isiani ,M. (2020) Social media and the Covid-19 pandemic: Observations from Nigeria. Cogent Arts &Humanities, (7) 1. doi: 10.1080/23311983.2020.1799483

Ashish, G., Latika, G. (2020). Social Media in the Times of COVID-19. Journal of Clinical Rheumatology, 26 (6), 220-223.doi: 10.1097/RHU.0000000000001508

Aslam, F., Awan, T., Syed, J, Khashif, A., Parveen,M. (2020). Sentiments and emotions evoked by news headlines of coronavirus disease (COVID-19) outbreak. Humanit Soc Sci Commun (7), 23 .doi.org/10.1057/s41599-020-0523-3

Bin-Nashwan, A. & Al-Daihani, M. (2020).Fundraising campaigns via social media platforms for mitigating the impacts of the COVID-19 epidemic. Journal of Islamic Marketing, 1106-y-.doi-org.mplbci.ekb.eg/10.1108/JIMA-07-2020-0200.

 

Bolarinwa, A., Olagunju, O., Babalola, T., Saeed, Q. (2020). Socio-demographic predictors of adherence to 2019 coronavirus prescribed recommendations and lockdown psychological impacts: Perspectives of Nigerian social media users. Journal of Public Health Research, 9(4), 490–495. doi.org/10.4081/jphr.2020.1864

 

Bojja, G., Ofori, M., Liu, J., Ambati, L.(2020). Early Public Outlook on the Coronavirus Disease (COVID-19): A Social Media Study. .Amcis. Proceedings .https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/resource/en/covidwho-746310

Bose, R. & Aithal, S. , Roy, S. (2020). Sentiment Analysis on the Basis of Tweeter Comments of Application of Drugs by Customary Language Toolkit and TextBlob Opinions of Distinct Countries. International Journal of Emerging Trends in Engineering Research. 8. doi: 10.30534/ijeter/2020/129872020.

Bowles, J., Larreguy, H., Liu, S. (2020). Countering misinformation via WhatsApp: Preliminary evidence from the COVID-19 pandemic in Zimbabwe. PLoS ONE, 1–11. doi.org/10.1371/journal.pone.0240005

 

Budhwani, H., & Sun, R. (2020). Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the "Chinese virus" on Twitter: Quantitative Analysis of Social Media Data. Journal of medical Internet research, 22(5). https://doi.org/10.2196/19301

 

Cauberghe, V, Van Wesenbeeck, I. De Jans, S. Hudders, L. Ponnet, K.(2020). How Adolescents Use Social Media to Cope with Feelings of Loneliness and Anxiety During COVID-19 Lockdown. CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING. doi: 10.1089/cyber.2020.0478

Chakra, K. , Bhatia, S., Bhattacharyya, S. , Platos, J. , Bag, R. , Hassanien, A. (2020). Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media. Applied Soft Computing. 97.doi: 10.1016/j.asoc.2020.106754.

 

Cheng, X ., Cao, Q ., Liao, S. (2020). An overview of literature on COVID-19, MERS and SARS: Using text mining and latent Dirichlet allocation. Journal of Information Science. Doi:10.1177/0165551520954674

Chivers, B., Garad, R., Boyle, J., Skouteris, H., Teede, H., Harrison, C.(2020) Perinatal Distress During COVID-19: Thematic Analysis of an Online Parenting Forum .J Med Internet Res .22(9):e22002. DOI: 10.2196/22002

Das, S. & Dutta, A. (2020). Characterizing public emotions and sentiments in COVID-19 environment: A case study of India. Journal of Human Behavior in the Social Environment .1(14). https://doi.org/10.1080/10911359.2020.1781015

Dua, AB ., Kilian, A ., Grainger, R ., Fantus, SA . ,Wallace, ZS ., Buttgereit, F ., Jonas, BL. (2020). Challenges, collaboration, and innovation in rheumatology education during the Covid 19 pandemic: leveraging new ways to teach .CLINICAL RHEUMATOLOGY,(39)5,3535-3541. DOI: 10.1007/s10067-020-05449-x

Effendi, M. I., Sugandini, D., Istanto,Y. (2020). Social Media Adoption in SMEs Impacted by COVID-19: The TOE Model. The Journal of Asian Finance, Economics, and Business, 7(11), 915–925. doi.org/10.13106/JAFEB.2020.VOL7.NO11.915

Essam, B.& Abdo, M.(2020) How Do Arab Tweeters Perceive the COVID-19 Pandemic? J Psycholinguist Res. 14,1–15. doi: 10.1007/s10936-020-09715-6.

Fan, L., Yu, H., Yin, Z. (2020).Stigmatization in social media: Documenting and analyzing hate speech for COVID-19 on Twitter. Proc Assoc Inf Sci Technol. 57(1):e313. doi: 10.1002/pra2.313.

Frazindar, A.(2019). Natural language processing for social media. https://www.kdnuggets.com/2019/02/natural-language-processing-social-media.html

Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., Wang, Y., Fu, H., Dai, J. (2020). Mental health problems and social media exposure during COVID-19 outbreak. PLoS ONE, 15(4), 1–10. https://doi.org/10.1371/journal.pone.0231924

Gupta, M., Bansal, A., Jain, B., Rochelle, J., Oak, A., Jalali, MS. (2020).Whether the Weather Will Help Us Weather the COVID-19 Pandemic: Using Machine Learning to Measure Twitter Users’ Perceptions. International Journal of Medical Informatics.145. https://doi.org/10.1016/j.ijmedinf.2020.104340

Hamoui, B.,Alashaikh, A.,Alanazi.(2020). COVID-19: What Are Arabic Tweeters Talking About?. Computational Data and Social Networks. 15757. 425- 436.doi.10.1007/978-3-030-66046-8_35

Hossain M., Ahammed B., Chanda S., Jahan N., Ela M., Islam M. (2020) Social and electronic media exposure and generalized anxiety disorder among people during COVID-19 outbreak in Bangladesh: A preliminary observation. PLoS ONE. 15(9).doi.org/10.1371/journal.pone.0238974.

Hung, M., Lauren, E., Hon, ES., Birmingham, WC., Xu, J., Su, S., Hon, SD., Park, J., Dang, P., Lipsky, MS.(2020) .Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence. J Med Internet Res .22(8).DOI: 10.2196/22590

 

Jimenez, M., Gomez, C. Soto, E. (2020). Coronavirus, Ageism, and Twitter: An Evaluation of Tweets about Older Adults and COVID-19. J Am Geriatr Soc. 68(8):1661-1665. doi: 10.1111/jgs.16508

Kaila, R. & Prasad, A. ( 2020) . Informational Flow on Twitter – Corona Virus Outbreak – Topic Modelling Approach .International Journal of Advanced Research in Engineering and Technology (IJARET), 11 (3), 2020. 128-134., Available at SSRN: https://ssrn.com/abstract=3565169.

Karami, A. & Anderson, M. (2020). Social media and COVID ‐19: Characterizing anti‐quarantine comments on Twitter. Proceedings of the Association for Information Science and Technology. 57.Doi: 10.1002/pra2.349.

Khan, R. , Shrivastava, P. , Kapoor, A , Tiwari, A. , Mittal, A. (2020). Social Media analysis with AI: sentiment analysis techniques for the analysis of Twitter Covid-19 data. Journal of Critical Reviews. 7(9). https://www.researchgate.net/publication/343685163.

Khan, Mohamed.( 2014), revitalization of the public sphere; A comparison between Habermasian and the new public sphere. AUDC, 8(1),41-57. Retrieved from: www.ebscohost.com ,Retrived in Jan 201

Kim, D.& Kim, J. (2014). Public opinion mining on social media: A case study of Twitter opinion on nuclear power. Advanced science and technology letters,51(CES-CUBE 2014), 224-228.https://doi.org/10.14257/astl.2014.51.

Koh J.& Liew, T.(2020). How loneliness is talked about in social media during COVID-19 pandemic: Text mining of 4,492 Twitter feeds. J Psychiatr Res. doi: 10.1016/j.jpsychires.2020.11.015.

Kralj ,P., Smailović,J., Sluban,B, Mozetič,I.(2015). Sentiment of Emojis. PLOS ONE 10(12).DOI:10.1371/journal.pone.0144296

Kaur, R. & Ranjan, S. (2020). Sentiment Analysis of 21 daysCOVID-19 Indian lockdown tweets.37-41 https://www.researchgate.net/publication/343064173_Sentiment_Analysis_of_21_daysCOVID-19_Indian_lockdown_tweets.

Lee, S.T.& Kim.(2020).H.S. Nation branding in the COVID-19 era: South Korea’s pandemic public diplomacy. Place Brand Public. https://doi.org/10.1057/s41254-020-00189-w 

Leidig, P.( 2020). What is social media analytics? Why is it important?. https://netbasequid.com/blog/what-is-social-media-analytics-why-is-it-important/

Lisitsa, E., Benjamin,K.,Chun,S.,Skalisky,J, Hammond,L, Mezulis,A.(2020).Loneliness among young adults during Covid-19 pandemic: the mediational roles of social media use and social support seeking. Published https://doi.org/10.1521/jscp.2020.39.8.708

Low, D., Rumker, L., Talkar, T., Torous, J., Cecchi, G., Ghosh, S. (2020). Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study. J Med Internet Res 22(10).DOI: 10.2196/22635

Miranda,C. , Viniegra,L. Liang,L. ( 2020) .Online Discourse in the Context of COVID-19, the First Health Crisis in China after the Advent of Mobile Social Media: A Content Analysis of China’s Weibo and Baidu. Social Sciences, MDPI. 9(10). 1-18. https://ideas.repec.org/a/gam/jscscx/v9y2020i10p167-d418876.html

Mutanga,M. &  Abayomi,A. (2020) .Tweeting on COVID-19 pandemic in South Africa: LDA-based topic modelling approach. African Journal of Science, Technology, Innovation and Development. 1(10). 2042 -1338. https://doi.org/10.1080/20421338.2020.1817262.

Murri, R., Segala, F. V., Del Vecchio, P., Cingolani, A., Taddei, E., Micheli, G., Fantoni, M. (2020). Social media as a tool for scientific updating at the time of COVID pandemic: Results from a national survey in Italy. PLoS ONE, 15(9), 1–7. https://doi.org/10.1371/journal.pone.0238414

Ong, C. J., Orfanoudaki, A., Zhang, R., Caprasse, F. P. M., Hutch, M., Ma, L., Fard, D., Balogun, O., Miller, M. I., Minnig, M., Saglam, H., Prescott, B., Greer, D. M., Smirnakis, S., Bertsimas, D. (2020). Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports. PLoS ONE, 15(6), 1–16. https://doi.org/10.1371/journal.pone.023490

Osakwe, Z., Ikhapoh, I., Arora, B., Bubu, O.(2020). Identifying public concerns and reactions during the COVID-19 pandemic on Twitter: A text-mining analysis. Public Health Nurs. 30.doi: 10.1111/phn.12843.

Oyebode, O. , Ndulue, C. , Adib, A ., Mulchandani, D. , Suruliraj, B. , Orji, F. , Chambers, C. , Meier, S. , Orji, R. (2020). Health, Psychosocial, and Social issues emanating from COVID-19 pandemic based on Social Media Comments using Natural Language Processing .arXiv e-prints-12144. Doi:10.2196/preprints.22734.

Pokharel, B. (2020). Twitter Sentiment analysis during COVID-19 Outbreak in Nepal. https://www.researchgate.net/publication/342158267_Twitter_Sentiment_analysis_during_COVID-19_Outbreak_in_Nepal

Schillinger, D.,Chittamuru,R. , Ramírez,S.( 2020) From “Infodemics” to Health Promotion: A Novel Framework for the Role of Social Media in Public Health. American Journal of Public Health. 110, 1393_1396, https://doi.org/10.2105/AJPH.2020.305746.

Stechemesser, A. , Wenz, L ., Levermann, A. (2020). Corona crisis fuels racially profiled hate in social media networks. EClinicalMedicine. 23. doi. 10.1016/j.eclinm.2020.100372

Steinert, S. (2020).Corona and value change. The role of social media and emotional contagion. Ethics Info Technol. https://doi.org/10.1007/s10676-020-09545-z

Tan T., Huang T., Wang X., Zuo Z.(2020). A preliminary investigation of COVID-19 transmission in the United States by incorporating social media sentiments. Proc Assoc Inf Sci Technol. 57(1). doi: 10.1002/pra2.370.

Thelwall, M. & Levitt, M.(2020). Retweeting Covid-19 disability issues: Risks, support and outrage. El profesional de la información. 29(2). 2. https://doi.org/10.3145/epi.2020.mar.16

Thelwall, M., & Thelwall, S. (2020). Covid-19 tweeting in English: Gender differences. Profesional De La Información, 29(3). https://doi.org/10.3145/epi.2020.may.01.

Ward, R., Riordan, B., Merrill, J., Raubenheimer, J.(2020). Describing the impact of the COVID-19 pandemic on alcohol-induced blackout tweets. Drug Alcohol Rev. 6(10).doi: 10.1111/dar.13186.

Wicke P. & Bolognesi M.(2020). Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PLoS ONE. 15(9). https://doi.org/10.1371/journal.pone.0240010

Wrycza,S. & Maślankowski,J. (2020). Social Media Users’ Opinions on Remote Work during the COVID-19 Pandemic; Thematic and Sentiment Analysis. Information Systems Management, 37(4), 288-297, DOI: 10.1080/10580530.2020.1820631

Xue J., Chen J., Chen C., Zheng C., Li S. (2020). Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter. PLOS ONE. 15(9).https://doi.org/10.1371/journal.pone.0239441

Yin, H. , Yang, S. , Li, J. (2020). Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media. https://www.researchgate.net/publication/342733537_Detecting_Topic_and_Sentiment_Dynamics_Due_to_COVID-19_Pandemic_Using_Social_Media

Zhao, Y., Cheng, S., Yu, X., Xu, H.(2020) Chinese Public's Attention to the COVID-19 Epidemic on Social Media: Observational Descriptive Study. J Med Internet Res 22(5). DOI: 10.2196/18825

Zhong,B. , Huang,Y , Liu,Q.(2021).Mental health toll from the coronavirus: Social media usage reveals Wuhan residents’ depression and secondary trauma in the COVID-19 outbreak. Computers in Human Behavior.114, https://doi.org/10.1016/j.chb.2020.106524ـ