A Content and Sentiment Analysis of Greek Tweets during the Pandemic
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Yousri Marzouki & Fatimah Salem Aldossari & Giuseppe A. Veltri, 2021. "Understanding the buffering effect of social media use on anxiety during the COVID-19 pandemic lockdown," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
- Jorge Carrillo-de-Albornoz & Javier Rodríguez Vidal & Laura Plaza, 2018. "Feature engineering for sentiment analysis in e-health forums," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-25, November.
- Martin Haselmayer & Marcelo Jenny, 2017. "Sentiment analysis of political communication: combining a dictionary approach with crowdcoding," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2623-2646, November.
- Meena Rambocas & João Gama, 2013. "Marketing Research: The Role Of Sentiment Analysis," FEP Working Papers 489, Universidade do Porto, Faculdade de Economia do Porto.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Jingjing Gao & Gabriela A. Gallegos & Joe F. West, 2023. "Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S," IJERPH, MDPI, vol. 20(21), pages 1-14, October.
- Ortal Slobodin & Ilia Plochotnikov & Idan-Chaim Cohen & Aviad Elyashar & Odeya Cohen & Rami Puzis, 2022. "Global and Local Trends Affecting the Experience of US and UK Healthcare Professionals during COVID-19: Twitter Text Analysis," IJERPH, MDPI, vol. 19(11), pages 1-17, June.
- Fernando Arias & Ariel Guerra-Adames & Maytee Zambrano & Efraín Quintero-Guerra & Nathalia Tejedor-Flores, 2022. "Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
- Dorit Zimand-Sheiner & Shalom Levy & Eyal Eckhaus, 2021. "Exploring Negative Spillover Effects on Stakeholders: A Case Study on Social Media Talk about Crisis in the Food Industry Using Data Mining," Sustainability, MDPI, vol. 13(19), pages 1-16, September.
- Vasiliki Vrana & Dimitrios Kydros & Iordanis Kotzaivazoglou & Ioanna Pechlivanaki, 2023. "EU Citizens’ Twitter Discussions of the 2022–23 Energy Crisis: A Content and Sentiment Analysis on the Verge of a Daunting Winter," Sustainability, MDPI, vol. 15(2), pages 1-22, January.
- Hyo-Sun Jung & Hye-Hyun Yoon & Min-Kyung Song, 2021. "A Study on Dining-Out Trends Using Big Data: Focusing on Changes since COVID-19," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Hiroki Takikawa & Takuto Sakamoto, 2020. "The moral–emotional foundations of political discourse: a comparative analysis of the speech records of the U.S. and the Japanese legislatures," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 547-566, April.
- Ali B. Mahmoud & Dieu Hack-Polay & Nicholas Grigoriou & Iris Mohr & Leonora Fuxman, 2021. "A generational investigation and sentiment and emotion analyses of female fashion brand users on Instagram in Sub-Saharan Africa," Journal of Brand Management, Palgrave Macmillan, vol. 28(5), pages 526-544, September.
- Reem ALBayari & Sherief Abdallah, 2022. "Instagram-Based Benchmark Dataset for Cyberbullying Detection in Arabic Text," Data, MDPI, vol. 7(7), pages 1-11, June.
- Rauh, Christian, 2018. "Validating a sentiment dictionary for German political language—a workbench note," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(4), pages 319-343.
- Elena G. Popkova & Aleksei V. Bogoviz & Svetlana V. Lobova & Abdula M. Chililov & Anastasia A. Sozinova & Bruno S. Sergi, 2022. "Changing entrepreneurial attitudes for mitigating the global pandemic’s social drama," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
- Griffith, David A. & Lee, Hannah S. & Yalcinkaya, Goksel, 2023. "Understanding the relationship between the use of social media and the prevalence of anxiety at the country level: a multi-country examination," International Business Review, Elsevier, vol. 32(4).
- Silvia Garc'ia-M'endez & Francisco de Arriba-P'erez & Ana Barros-Vila & Francisco J. Gonz'alez-Casta~no, 2024. "Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages," Papers 2404.08665, arXiv.org.
- Juha Koljonen & Emily Öhman & Pertti Ahonen & Mikko Mattila, 2022. "Strategic sentiments and emotions in post-Second World War party manifestos in Finland," Journal of Computational Social Science, Springer, vol. 5(2), pages 1529-1554, November.
- Eyal Eckhaus & Zachary Sheaffer, 2018. "Managerial hubris detection: the case of Enron," Risk Management, Palgrave Macmillan, vol. 20(4), pages 304-325, November.
- Vagianos Dimitrios & Koutsoupias Nikos, 2021. "Framing Coworking Spaces Marketing Strategies via Social Media Indices," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(2), pages 1-14, June.
- Shisei Tei & Junya Fujino, 2022. "Social ties, fears and bias during the COVID-19 pandemic: Fragile and flexible mindsets," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-7, December.
- Wolfinger, Julia & Köhler, Ekkehard A. & Feld, Lars P. & Thomas, Tobias, 2018.
"57 Channels (And Nothin On): Does TV-News on the Eurozone affect Government Bond Yield Spreads?,"
VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy
181610, Verein für Socialpolitik / German Economic Association.
- Julia Wolfinger & Lars P. Feld & Ekkehard A. Köhler & Tobias Thomas, 2018. "57 Channels (And Nothin On) - Does TV-News on the Eurozone Affect Government Bond Yield Spreads?," CESifo Working Paper Series 7437, CESifo.
- Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
- Shesen Guo & Ganzhou Zhang, 2020. "Using Machine Learning for Analyzing Sentiment Orientations Toward Eight Countries," SAGE Open, , vol. 10(3), pages 21582440209, August.
- Katja Pietrzyck & Nora Berke & Vanessa Wendel & Julia Steinhoff-Wagner & Sebastian Jarzębowski & Brigitte Petersen, 2021. "Understanding the Importance of International Quality Standards Regarding Global Trade in Food and Agricultural Products: Analysis of the German Media," Agriculture, MDPI, vol. 11(4), pages 1-20, April.
- Kim, Jikyung (Jeanne) & Dong, Hang & Choi, Jeonghye & Chang, Sue Ryung, 2022. "Sentiment change and negative herding: Evidence from microblogging and news," Journal of Business Research, Elsevier, vol. 142(C), pages 364-376.
- Hirsch, Patrick & Feld, Lars P. & Köhler, Ekkehard A. & Thomas, Tobias, 2024.
"“Whatever It Takes!” How tonality of TV-news affected government bond yield spreads during the European debt crisis,"
European Journal of Political Economy, Elsevier, vol. 82(C).
- Patrick Hirsch & Lars P. Feld & Ekkehard A. Köhler & Tobias Thomas, 2024. "“Whatever It Takes!” How Tonality of TV-News Affected Government Bond Yield Spreads during the European Debt Crisis," CESifo Working Paper Series 10980, CESifo.
- Siyao Liu & Bin Yu & Chan Xu & Min Zhao & Jing Guo, 2022. "Characteristics of Collective Resilience and Its Influencing Factors from the Perspective of Psychological Emotion: A Case Study of COVID-19 in China," IJERPH, MDPI, vol. 19(22), pages 1-19, November.
- Divine Q. Agozie & Muesser Nat, 2022. "Do communication content functions drive engagement among interest group audiences? An analysis of organizational communication on Twitter," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
- Robert Hogenraad, 2019. "Fear in the West: a sentiment analysis using a computer-readable “Fear Index”," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1239-1261, May.
More about this item
Keywords
COVID-19; coronavirus; pandemic; discussion; Twitter; social network analysis; sentiment analysis;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:6150-:d:565450. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.