Covid-19 tweeting in English: Gender differences



Palabras clave:

Covid-19, Coronavirus, Twitter, Gender, Public health information.


At the start of 2020, Covid-19 became the most urgent threat to global public health. Uniquely in recent times, governments have imposed partly voluntary, partly compulsory restrictions on the population to slow the spread of the virus. In this context, public attitudes and behaviors are vitally important for reducing the death rate. Analyzing tweets about the disease may therefore give insights into public reactions that may help guide public information campaigns. This article analyses 3,038,026 English tweets about Covid-19 from March 10 to 23, 2020. It focuses on one relevant aspect of public reaction: gender differences. The results show that females are more likely to tweet about the virus in the context of family, social distancing and healthcare, whereas males are more likely to tweet about sports cancellations, the global spread of the virus, and political reactions. Thus, women seem to be taking a disproportionate share of the responsibility for directly keeping the population safe. The detailed results may be useful to inform public information announcements and to help understand the spread of the virus. For example, failure to impose a sporting bans whilst encouraging social distancing may send mixed messages to males.


Los datos de descargas todavía no están disponibles.

Biografía del autor/a

Mike Thelwall, University of Wolverhampton

Mike Thelwall is the head of the Statistical Cybermetrics Research Group at the University of Wolverhampton, UK. He has developed a wide range of software for gathering and analysing web data, including hyperlink analysis, sentiment analysis and content analysis for Twitter, YouTube, MySpace, blogs and the web in general.

Saheeda Thelwall, University of Wolverhampton

Senior lecturer in adult nursing, with a focus on public health.


Argamon, Shlomo; Koppel, Moshe; Fine, Jonathan; Shimoni, Anat-Rachel (2003). "Gender, genre, and writing style in formal written texts". Text, v. 23, n. 3, pp. 321-346.

Benjamini, Yoav; Hochberg, Yusuf (1995). "Controlling the false discovery rate: a practical and powerful approach to multiple testing". Journal of the Royal Statistical Society: Series B (Methodological), v. 57, n. 1, pp. 289-300.

Bode, Leticia (2017). "Closing the gap: gender parity in political engagement on social media". Information, communication & society, v. 20, n. 4, pp. 587-603.

Carers UK (2020). 10 facts about women and caring in the UK on International women´s day.

Cinelli, Matteo; Quattrociocchi, Walter; Galeazzi, Alessandro; Valensise, Carlo-Michele; Brugnoli, Emanuele; Schmidt, Ana-Lucia; Zola, Paola; Zollo, Fabiana; Scala, Antonio (2020). "The covid-19 social media infodemic". arXiv preprint arXiv:2003.05004.

Family Caregiver Alliance (2020). Caregiver statistics: Demographics.

Karimi, Fariba; Wagner, Claudia; Lemmerich, Florian; Jadidi, Mohsen; Strohmaier, Markus (2016). "Inferring gender from names on the web: A comparative evaluation of gender detection methods". In: Proceedings of the 25th International conference companion on World Wide Web (pp. 53-54).

Kulshrestha, Juhi; Kooti, Farshad; Nikravesh, Ashkan; Gummadi, Krishna P. (2012). "Geographic dissection of the Twitter network". In: Sixth international AAAI conference on weblogs and social media.

Lau, Joseph; Yang, Xilin; Tsui, Hiyi; Pang, Ellie (2004). "SARS related preventive and risk behaviours practised by Hong Kong-mainland China cross border travellers during the outbreak of the SARS epidemic in Hong Kong". Journal of epidemiology & community health, v. 58, n. 12, pp. 988-996.

Leblanc, Vicky; Bégin, Catherine; Hudon, Anne-Marie; Royer, Marie-Michelle; Corneau, Louise; Dodin, Sylvie; Lemieux, Simone (2014). "Gender differences in the long-term effects of a nutritional intervention program promoting the Mediterranean diet: changes in dietary intakes, eating behaviors, anthropometric and metabolic variables". Nutrition journal, v. 13, n. 1, article 107.

Li, Sijia; Wang, Yilin; Xue, Jia; Zhao, Nan; Zhu, Tingshao (2020). "The impact of Covid-19 epidemic declaration on psychological consequences: A study on active Weibo users". International journal of environmental research and public health, v. 17, n. 6, article 2032.

Lipsitch, Marc; Swerdlow, David; Finelli, Lyn (2020). "Defining the epidemiology of Covid-19 - studies needed". New England journal of medicine, n. 382, pp. 1194-1196.

Luhn, Hans (1960). "Key word"in"context index for technical literature (kwic index)". American documentation, v. 11, n. 4, pp. 288-295.

Parker, Kim; Horowitz, Juliana; Rohal, Molly (2015). Parenting in America: Outlook, worries, aspirations are strongly linked to financial situation. Pew Research Center.

Plaza, Mélissa; Boiché, Julie; Brunel, Lionel; Ruchaud, Franí§ois (2017). "Sport = male"¦ But not all sports: Investigating the gender stereotypes of sport activities at the explicit and implicit levels". Sex roles, v. 76, n. 3-4, pp. 202-217.

Reinhardt, Susa; Bischof, Gallus; Grothues, Janina; John, Ulrich; Meyer, Christian; Rumpf, Hans-Jí¼rgen (2008). "Gender differences in the efficacy of brief interventions with a stepped care approach in general practice patients with alcohol-related disorders". Alcohol & alcoholism, v. 43, n. 3, pp. 334-340.

Schaeffer, Katherine (2019). U.S. has changed in key ways in the past decade, from tech use to demographics. Pew Research Center.

Smith, Aaron; Hughes, Adam; Remy, Emma; Shah, Sono (2020). Democrats on Twitter more liberal, less focused on compromise than those not on the platform. Pew Research Center.

Smith, Adam; Wojcik, Stefan (2019). 10 facts about Americans and Twitter. Pew Research Center.

Thelwall, Mike; Bailey, Carol; Makita, Meiko; Sud, Pardeep; Madalli, Devika P. (2019). "Gender and research publishing in India: Uniformly high inequality?". Journal of informetrics, v. 13, n. 1, pp. 118-131.

Thelwall, Mike; Bailey, Carol; Tobin, Catherine; Bradshaw, Noel-Ann (2019). "Gender differences in research areas, methods and topics: Can people and thing orientations explain the results?". Journal of informetrics, v. 13, n. 1, pp. 149-169.

Thelwall, Mike; Levitt, Jonathan (2020). "Retweeting Covid-19 disability issues: Risks, support and outrage". El profesional de la información, v. 29, n. 2, e290216.

Thelwall, Mike; Stuart, Emma (2019). "She´s Reddit: A source of statistically significant gendered interest information?". Information processing & management, v. 56, n. 4, pp. 1543-1558.

Thelwall, Mike (2018). "Can museums find male or female audiences online with YouTube?". Aslib journal of information management, v. 70, n. 5, pp. 481-497.

Thelwall, Mike (2020). "Gender differences in Covid-19 tweeting in English". FigShare.




Cómo citar

Thelwall, M., & Thelwall, S. (2020). Covid-19 tweeting in English: Gender differences. Profesional De La información, 29(3).



Artí­culos de investigación Covid-19 / Covid-19 research articles