Article

TWITTER AS A TOOL TO MONITOR ATTITUDES: THE STRATEGIC USAGE OF SOCIAL MEDIA🔗

TWITTER COMO HERRAMIENTA PARA LA MONITORIZACIÓN DE ACTITUDES: EL USO ESTRATÉGICO DE LAS REDES SOCIALES🔗

English Full Article Citation
Paper Selected at International Conference on Innovative Education in Business and Economics (ICIEBE 2022)

Author(s)🔗

Jorge Villagrasa EDEM Business School, Spain
Colin Donaldson EDEM Business School, Spain
Cortes López Medina Ontinyent Hospital, Spain

https://doi.org/10.35564/jmbe.2022.0023

Abstract🔗

This research delves into Twitter analysis, a well-known social media messaging service recently acquired by Elon Musk for $44bn, which we argue to enable researchers to better monitor (and try to solve) the status of the general population regarding the type of user and content of the received messages. With this analysis, it is intended to show the possibility of disseminating reliable, immediate, and high-quality messages (that would be unlikely obtained through official information channels), potentially provoking in this way an exponential impact afterwards. This idea in particular is key, due to any average social media population user and especially from 'Gen Z' (which hold 25% lower attention capacity and 40% lower check of the reliability of sources than its predecessor generation) could easily understand wrongly the massive (and unfiltered) amounts of information received, therefore generating false alarms, beliefs and in some cases, even own welfare losses.
To do so, along this paper we propose the development of a pedagogical activity with a multi-methodological approach through which to carry out a qualitative (and cross-sectional) analysis in the degree of ‘Business Administration and Management’ of EDEM-Business School. Thus, the aforementioned activity would constitute a successful teaching innovation exercise as regards to the acquisition of the required competencies and learning outcomes established within the course, as well as to the achievement of a (attainable and consensual) solution to a real problem faced nowadays and selected by the students: in this case, the increase of awareness about the cervical cancer, a type of cancer that is currently the fourth most common among women worldwide and one of the easiest to prevent through screening tests.

Keywords
monitor attitudes, awareness, strategic usage, social media, Twitter

Resumen🔗

El presente estudio profundiza en el análisis de Twitter, una conocida red social de mensajería adquirida recientemente por Elon Musk por 44.000 millones de dólares, a través de la cual se consigue fácilmente monitorizar (e intentar resolver) el estado general de la población en función del tipo de usuario y contenido de los mensajes recibidos. Con este análisis, se pretende mostrar la posibilidad de difundir mensajes fiables, de forma inmediata y de calidad (que difícilmente se obtendrían a través de los canales oficiales de información), provocando así potencialmente un impacto exponencial a posteriori. Esta idea en particular es muy relevante, debido a que cualquier usuario promedio de las redes sociales y especialmente de la 'Generación Z' (los cuales poseen un 25% menos de capacidad de atención y verifican un 40% menos la fiabilidad de las fuentes consultadas que su generación anterior) podría fácilmente entender de forma errónea la ingente cantidad de información recibida (y sin filtrar), generando por tanto posibles falsas alarmas, creencias y, en algunos casos, incluso pérdidas propias de bienestar.
Para ello, a lo largo de este trabajo proponemos el desarrollo de una actividad pedagógica con un enfoque multimetodológico a través de la cual llevar a cabo un análisis cualitativo (y transversal) dentro del grado de ‘Administración y Dirección de Empresas’ de EDEM-Escuela de Empresarios. De esta forma, la actividad mencionada constituiría un ejercicio de éxito dentro de la innovación docente a la hora de adquirir las competencias requeridas y los resultados de aprendizaje establecidos dentro la asignatura, así como la consecución de una solución (alcanzable y consensuada) a un problema real seleccionado por los estudiantes y al que se enfrentan en la actualidad: en este caso, el aumento de la concienciación sobre el cáncer de cuello de útero, un tipo de cáncer que actualmente es el cuarto más común entre las mujeres en todo el mundo y de los más fáciles de prevenir a través de exámenes de detección.

Palabras clave
monitorizar actitudes, concienciación, uso estratégico, redes sociales, Twitter

Received
15 November 2022

Accepted
23 December 2022

Copyright
This is an open access article under the CC BY-NC license.

Citation🔗

Villagrasa, J.; Donaldson, C.; & López, C. (2022). Twitter as a tool to monitor attitudes: the strategic usage of social media. Journal of Management and Business Education, 5(4), 392-423. https://doi.org/10.35564/jmbe.2022.0023

References🔗

Abiodun, O. A.; Fatungase, O. K.; Olu-Abiodun, O. O.; Idowu-Ajiboye, B. A.; & Awosile, J. O. (2013). An assessment of women’s awareness and knowledge about cervical cancer and screening and the barriers to cervical screening in Ogun State, Nigeria. Journal of Medical and Dental Sciences, 10(3), pp. 52-58. https://doi.org/10.9790/0853-1035258
Anderson, B.; & Speed, E. (2010). Social media and health: implications for primary health care providers. Report to Solihull Care Trust. Retrieved from http://repository.essex.ac.uk/3453/2/SCT-DI-D1.2-Social-Media-Final.pdf [accessed on 25 August 2022]
Appel, G.; Grewal, L.; Hadi, R.; & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79-95. https://doi.org/10.1007/s11747-019-00695-1
Aswathy, S.; Quereshi, M. A.; Kurian, B.; & Leelamoni, K. (2012). Screening for Breast Cancer in a Low Middle Income Country: Predictors in a Rural Area of Kerala, India. Indian Journal of Medical Research, 136(2), pp. 205-210. https://doi.org/10.7314/apjcp.2014.15.5.1919
Augusto, E. F.; Rosa, M. L.; Cavalcanti, S. M.; & Oliveira, L. H. (2013). Barriers to cervical cancer screening in women attending the Family Medical Program in Niterói, Rio de Janeiro. Archives Gynecology Obstetrics, 287(1), pp. 53-58. https://doi.org/10.1007/s00404-012-2511-3
Babić Rosario, A.; Sotgiu, F.; De Valck, K.; & Bijmolt, T. H. (2016). The effect of electronic word of mouth on sales: A meta-analytic review of platform, product, and metric factors. Journal of Marketing Research, 53(3), 297-318. https://doi.org/10.1509/jmr.14.0380
Basu, P.; Hassan, S.; Fileeshia, F.; Mohamed, S.; Nahoodha, A.; Shiuna, A.; … ; & Saleem, F. J. (2014). Knowledge, Attitude and Practices of Women in Maldives Related to the Risk Factors, Prevention and Early Detection of Cervical Cancer. Asian Pacific Journal of Cancer Prevention Health, 15(16), pp. 6691-6695. https://doi.org/10.7314/apjcp.2014.15.16.6691
Bruni, L.; Barrionuevo-Rosas, L.; Albero, G.; Aldea, M.; Serrano, B.; Valencia, S.; … ; & Castellsagué, X. (2014). ICO Information Centre on HPV and Cancer (HPV Information Centre). Human Papillomavirus and Related Diseases in the World. Summary Report 2016-02-25. Retrieved from http://www.hpvcentre.net/statistics/reports/XWX.pdf [accessed on 6 December 2022]
Centres of Disease of Control. HPV - Associated cancers. (2016). Atlanta, GA: US Department of Health and Human Services, CDC. Retrieved from http://www.cdc.gov/cancer/hpv/ [accessed on 15 July 2018]
Chang, Y.; Li, Y.; Yan, J.; & Kumar, V. (2019). Getting more likes: The impact of narrative person and brand image on customer–brand interactions. Journal of the Academy of Marketing Science, 47(6), 1027-1045. https://doi.org/10.1007/s11747-019-00632-2
Chou, W. S.; Hunt, Y. M.; Beckjord, E. B.; Moser, R. P.; & Hesse, B. W. (2009). Social media use in the United States: implications for health communication. Journal of Medical Internet Research, 11(4): e48. https://doi.org/10.2196/jmir.1249
Christakis, N. A.; & Fowler, J. H. (2008). The collective dynamics of smoking in a large social network. New England Journal of Medicine, 358(21), pp. 2249-2258. https://doi.org/10.1056/nejmsa0706154
Conger, K.; & Hirsch, L. (2022). Elon Musk Completes $44 Billion Deal to Own Twitter. Retrieved from https://www.nytimes.com/2022/10/27/technology/elon-musk-twitter-deal-complete.html https://doi.org/10.54097/hbem.v2i.2399
Cossentino, J. (2005). Ritualizing expertise: A non-Montessorian view of the Montessori method. American Journal of Education, 111(2): 211-244. https://doi.org/10.1086/426838
Dhendup, T.; & Tshering, P. (2014). Cervical cancer knowledge and screening behaviors among female university graduates of year 2012 attending national graduate orientation program, Bhutan. BMC Women's health, 14(1), pp. 2-7. https://doi.org/10.1186/1472-6874-14-44
Enberg, J. (2018). Global Influencer Marketing. Retrieved from https://tinyurl.com/y7srumpm [accessed on 13 December 2022]
eMarketer (2018). Social Network Users and Penetration in Worldwide. Retrieved from https://tinyurl.com/ycr2d3v9 [accessed on 25 November 2022]
Fernández-Moya, M.; Cuadros, P. J.; Salvador, C.; & Pinar J. M. (2020) The Montessori method in university teaching, In INTED2020 Proceedings, pp. 3861-3864. https://doi.org/10.21125/inted.2020.1079
Fox, S.; & Jones, S. (2009). The social life of health information. Pew Internet. Retrieved from www.pewinternet.org/Reports/2009/8-The-Social-Life-of-Health-Information.aspx [accessed on 9 May 2022]
Fuster-Casanovas, A.; Das, R.; Vidal-Alaball, J.; Segui, F. L.; & Ahmed, W. (2022). The# VaccinesWork Hashtag on Twitter in the Context of the COVID-19 Pandemic: Network Analysis. JMIR Public Health and Surveillance, 8(10), e38153. https://doi.org/10.2196/38153
Google (2019). Generation Y and Z: characteristics and differences. Retrieved from https://www.thinkwithgoogle.com/intl/es-es/insights/tendencias-de-consumo/generaciones-y-y-generacion-z-en-que-se-diferencian-y-como-captar-su-atencion/ [accessed on 20 November 2022]
Gottlieb, M.; & Dyer, S. (2020). Information and disinformation: social media in the COVID‐19 crisis. Academic Emergency Medicine, 27(7), 640. https://doi.org/10.1111/acem.14036
Health Research Institute. (2012). Social media "likes" health care: from marketing to social business. Retrieved from http://www.healthyworkplaces.info/wp-content/uploads/2012/04/health-care-social-media-report.pdf [accessed on 25 September 2022]
Hutton, J. S.; Dudley, J.; Horowitz-Kraus, T.; DeWitt, T.; & Holland, S. K. (2020). Associations between screen-based media use and brain white matter integrity in preschool-aged children. JAMA pediatrics, 174(1): e193869-e193869. https://doi.org/10.1001/jamapediatrics.2019.3869
John, L. K.; Emrich, O.; Gupta, S.; & Norton, M. I. (2017). Does “liking” lead to loving? The impact of joining a brand's social network on marketing outcomes. Journal of marketing research, 54(1), 144-155. https://doi.org/10.1509/jmr.14.0237
Knoll, J.; & Matthes, J. (2017). The effectiveness of celebrity endorsements: a meta-analysis. Journal of the Academy of Marketing Science, 45(1), 55-75. https://doi.org/10.1007/s11747-016-0503-8
Kramer, R. (1976). Montessori: A Biography. New York, NY: Addison/Wesley. https://doi.org/10.1177/002248717602700229
Lapointe, L.; Ramaprasad, J.; & Vedel, I. (2014). Creating health awareness: a social media enabled collaboration. Health and Technology, 4(1), 43-57. https://doi.org/10.1007/s12553-013-0068-1
Le, G. M.; Radcliffe, K.; Lyles, C.; Lyson, H. C.; Wallace, B.; Sawaya, G.; ... ; & Sarkar, U. (2019). Perceptions of cervical cancer prevention on Twitter uncovered by different sampling strategies. PloS one, 14(2), e0211931. https://doi.org/10.1371/journal.pone.0211931
Learmonth, D.; De Abreu, C.; & Horsfall, H. (2013). Adherence barriers and facilitators for cervical screening amongst currently disadvantaged women in the greater Cape Town region of South Africa. African Journal of Primary Health Care & Family Medicine, 5(1), pp. 1-10. https://doi.org/10.4102/phcfm.v5i1.492
Lenoir, P.; Moulahi, B.; Azé, J.; Bringay, S.; Mercier, G.; & Carbonnel, F. (2017). Raising awareness about cervical cancer using Twitter: content analysis of the 2015# SmearForSmear campaign. Journal of medical Internet research, 19(10), https://doi.org/10.2196/jmir.8421
Lyles, C. R.; Goldbehere, A.; Le, G.; El Ghaoui, L.; & Sarkar, U. (2016). Applying Sparse Machine Learning Methods to Twitter: Analysis of the 2012 Change in Pap Smear Guidelines. A Sequential mixed-Methods Study. JMIR Public Health Surveill, 2(1): e21. https://doi.org/10.2196/publichealth.5308
Lyles, C. R.; Lopez, A.; Pasick, R.; & Sarkar, U. (2013). "5 mins of uncomfyness is better than dealing with cancer 4 a lifetime": an exploratory qualitative analysis of cervical and breast cancer screening dialogue on Twitter. Journal of Cancer Education, 28(1), pp. 127-33. https://doi.org/10.1007/s13187-012-0432-2
Ma, M.; & Morris, L. (2017). The agile innovation sprint. International Management Review, 13(1), 92. Retrieved from http://americanscholarspress.us/journals/IMR/pdf/IMR-1-2017.%20pdf/IMR-v13n1art8.pdf [accessed on 22 November 2022]
Maxim (2018). Every Selena Gomez Instagram post for puma is worth $3.4 million. Retrieved from https://tinyurl.com/ybr6nzok [accessed on 8 December 2022]
McNab, C. (2009). What social media offers to health professionals and citizens. Bulletin of the World Health Organization, 87(8), pp. 566-566. https://doi.org/10.2471/blt.09.066712
Mingers, J. (1997). Multi-paradigm multimethodology. In J. Mingers, & A. Gill (Eds.), Multimethodology: The theory and practice of combining management science methodologies (pp. 1-20). Chichester, UK: Wiley. https://doi.org/10.1002/1099-1743(200007/08)17:4<407::AID-SRES363>3.0.CO;2-A
Modahl, M.; Tompsett, L.; & Moorhead, T. (2011). Doctors, patients, and social media. Retrieved from http://www.quantiamd.com/qqcp/DoctorsPatientSocialMedia.pdf [accessed on 2 October 2022]
Montessori, M. (1995). The Absorbent Mind. New York: Henry Holt. ISBN9780805041569
Moore, R. J. (2009). Twitter data analysis: an investor’s perspective. Retrieved from http://techcrunch.com/2009/10/05/twitter-dataanalysis-an-investors-perspective-2/ [accessed on 29 Oct 2022]
Murad, R.; Hussin, S.; Yusof, R.; Miserom, S. F.; & Yaacob, M. H. (2019). A conceptual foundation for smart education driven by Gen Z. International Journal of Academic Research in Business and Social Sciences, 9(5): 1022-1029. https://doi.org/10.6007/ijarbss/v9-i2/5948
Neck, H. M.; Greene, P. G.; & Brush, C. G. (2014). Teaching entrepreneurship: A practice-based approach. Cheltenham, UK: Edward Elgar Publishing. ISBN9781782540557
Nidagundi, P.; & Novickis, L. (2017). Introducing lean canvas model adaptation in the scrum software testing. Procedia Computer Science, 104, 97-103. https://doi.org/10.1016/j.procs.2017.01.078
Niles, M. T.; Emery, B. F.; Reagan, A. J.; Dodds, P. S.; & Danforth, C. M. (2019). Social media usage patterns during natural hazards. PloS one, 14(2), e0210484. https://doi.org/10.1371/journal.pone.0210484
Pinar-Pérez, J. M.; Morales-Arsenal, R.; Fernandez-Moya, M.; Cuadros-Solas, P.; & Salvador, C. (2021). Mitigating deficiencies of generation Z through new educational methodologies in a business statistic course. In Proceedings INNODOCT/20. International Conference on Innovation, Documentation and Education, pp. 81-88. https://doi.org/10.4995/INN2020.2020.11821
Prier, K. W.; Smith, M. S.; Giraud-Carrier, C.; & Hanson, C. L. (2011). Identifying health-related topics on twitter. International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, pp. 18-25. https://doi.org/10.1007/978-3-642-19656-0_4
Riyal, R. N.; & Lapinski, M. K. (2009). Why health communication is important in public health. Bulletin Word Health Organization, 87, p. 247. https://doi.org/10.2471/BLT.08.056713
Rojas, R. M. R. (2022). Modelamiento de tópicos utilizando mensajes de Twitter relacionados al cáncer cervical. Interfases, 016, e5887-e5887. https://doi.org/10.26439/interfases2022.n016.5887
Signorini, A.; Segre, A. M.; & Polgreen, P. M. (2011). The use of Twitter to track levels of disease activity and public concern in the US during the influenza A H1N1 pandemic. PloS one, 6(5), e19467. https://doi.org/10.1371/journal.pone.0019467
Stephen, A. T.; & Galak, J. (2012). The effects of traditional and social earned media on sales: A study of a microlending marketplace. Journal of marketing research, 49(5), 624-639. https://doi.org/10.1509/jmr.09.0401
Sudenga, S. L.; Rositch, A. F.; Otieno, W. A.; & Smith, J. S. (2013). Knowledge, attitudes, practices and perceived risk of cervical cancer among Kenyan women: brief report. International Journal of Gynecol Cancer, 23(5), pp. 895-899. https://doi.org/10.1097/IGC.0b013e31828e425c
Teoh, D.; Shaikh, R.; Vogel, R. I.; Zoellner, T.; Carson, L.; Kulasingam, S.; & Lou, E. (2018). A cross-sectional review of cervical cancer messages on twitter during cervical cancer awareness month. Journal of lower genital tract disease, 22(1), 8. https://doi.org/10.1097/lgt.0000000000000363
Thackeray, R.; Burton, S. H.; Giraud-Carrier, C.; Rollins, S.; & Draper, C. R. (2013). Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month. BMC Cancer, 13: 508.https://doi.org/10.1186/1471-2407-13-508
Trusov, M.; Bucklin, R. E.; & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: findings from an internet social networking site. Journal of marketing, 73(5), 90-102.https://doi.org/10.1509/jmkg.73.5.90
Were, E.; Nyaberi, Z.; & Buziba, N. (2011). Perceptions of risk and barriers to cervical cancer screening at Moi Teaching and Referral Hospital (MTRH), Eldoret, Kenya. African Health Sciences, 11(1), pp. 58-64. PMC3092325 https://doi.org/10.4314/eamj.v78i2.9088
Winquist, J. R.; & Carlson, K. A. (2014). Flipped statistics class results: Better performance than lecture over one year later. Journal of Statistics Education, 22(3): 1-10. https://doi.org/10.1080/10691898.2014.11889717
Xu, S.; Markson, C.; Costello, K. L.; Xing, C. Y.; Demissie, K.; & Llanos, A. A. (2016). Leveraging Social Media to Promote Public Health Knowledge: Example of Cancer Awareness via Twitter. JMIR Public Health Surveill, 2(1): e17. https://doi.org/10.2196/publichealth.5205
Yip, P.; Xiao, Y.; Xu, Y.; Chan, E.; Cheung, F.; Chan, C. S.; & Pirkis, J. (2022). Social media sentiments on suicides at the New York City landmark, vessel: a Twitter study. International Journal of Environmental Research and Public Health, 19(18), 11694. https://doi.org/10.3390/ijerph191811694
Zhang, X. A.; & Cozma, R. (2022). Risk sharing on Twitter: Social amplification and attenuation of risk in the early stages of the COVID-19 pandemic. Computers in Human Behavior, 126, 106983. https://doi.org/10.1016/j.chb.2021.106983