The Hashtag #CharlasEducativas as a Teacher Affinity Space on Twitter

  1. Ingrid Mosquera-Gende 1
  2. Paula Marcelo-Martínez 2
  3. Ana Yara Postigo-Fuentes 3
  4. Manuel Fernández-Navas 4
  1. 1 Universidad Internacional de La Rioja
    info

    Universidad Internacional de La Rioja

    Logroño, España

    ROR https://ror.org/029gnnp81

  2. 2 Universidad de Sevilla
    info

    Universidad de Sevilla

    Sevilla, España

    ROR https://ror.org/03yxnpp24

  3. 3 Universidad de Düsseldorf
  4. 4 Universidad de Málaga
    info

    Universidad de Málaga

    Málaga, España

    ROR https://ror.org/036b2ww28

Revue:
Comunicar: Revista Científica de Comunicación y Educación

ISSN: 1134-3478

Année de publication: 2024

Titre de la publication: Empowered and hyper(dis)connected audiences: Actors, contexts, experiences and educommunicative practices

Número: 78

Pages: 222-233

Type: Article

DOI: 10.58262/V32I78.18 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

D'autres publications dans: Comunicar: Revista Científica de Comunicación y Educación

Résumé

Twitter has positioned itself as one of the social networks most used by teachers, generating teacher affinity spaces for them to share and collaborate. This study analyses the hashtag #CharlasEducativas, to explore whether it represents a teaching affinity space on this social network. It is a hashtag linked to an educational project created in Spain and related to all educational stages in a cross-cutting manner. Using a mixed methods research, 6073 tweets with the hashtag #CharlasEducativas, published between January 2020 and July 2022, were analysed, including a total of 761 Twitter profiles. Using the software MAXQDA, a category system was developed to classify the most frequent topics in the interactions and to study the tone of the discourse. The social network analysis software Graphext was used for in depth analysis of the profiles with the highest participation. It was confirmed that the characteristics of affinity spaces (collaboration, horizontal nature, creation of community, existence of hierarchy and source of informal learning) were met. The interactions linked to this hashtag are positive, friendly and with a close and relaxed tone, which favours the generation of a group feeling, facilitating informal learning. In addition, the space has a strong hierarchy with leadership roles that allows the information to f low and be fed continuously.

Références bibliographiques

  • Adedoyin, O. B., & Soykan, E. (2023). Covid-19 Pandemic and Online Learning: the Challenges and Opportunities. Interactive Learning Environments, 31(2), 863-875. https://doi.org/10.1080/10494820.2020.1813180
  • Antelmi, A., Malandrino, D., & Scarano, V. (2019). Characterizing the Behavioral Evolution of Twitter Users and the Truth Behind the 90-9-1 Rule. In Companion Proceedings of the 2019 World Wide Web Conference (pp. 1035-1038). ACM. https://doi.org/10.1145/3308560.3316705
  • Braun, V., & Clarke, V. (2021). To Saturate or Not to Saturate? Questioning Data Saturation as a Useful Concept for Thematic Analysis and Sample-size Rationales. Qualitative Research in Sport, Exercise and Health, 13(2), 201-216. https://doi.org/10.1080/2159676 X.2019.1704846
  • Burnap, P., & Williams, M. L. (2015). Cyber Hate Speech on Twitter: an Application of Machine Classification and Statistical Modeling for Policy and Decision Making. Policy & Internet, 7(2), 223-242. https://doi.org/10.1002/poi3.85
  • Carmona, C. E. (2020). Hacia La Inclusión Educativa en La Universidad: Diseño Universal Para El Aprendizaje Y La Educación De Calidad. Ediciones Octaedro. https://go.revistacomunicar.com/NIPmPh
  • Carolan, B. V. (Ed.). (2013). Social Network Analysis and Education: Theory, Methods & Applications. Sage Publications. https://doi.org/10.4135/9781452270104
  • Carpenter, J. P., & Krutka, D. G. (2014). How and Why Educators Use Twitter: a Survey of the Field. Journal of Research on Technology in Education, 46(4), 414- 4 34. https://doi.org/10.1080/15391523.2014.925701
  • Carpenter, J. P., Morrison, S. A., Rosenberg, J. M., & Hawthorne, K. A. (2023). Using Social Media in Pre-service Teacher Education: the Case of a Program-wide Twitter Hashtag. Teaching and Teacher Education, 124, 104036. https://doi.org/10.1016/j.tate.2023.104036
  • Çeliktuğ, M. F. (2018). Twitter Sentiment Analysis, 3-way Classification: Positive, Negative or Neutral? In 2018 IEEE International Conference on Big Data (Big Data) (pp. 2098-2103). IEEE. https://doi.org/10.1109/BigData.2018.8621970
  • Daly, A. J., Liou, Y.-H., Fresno, M. D., Rehm, M., & Bjorklund Jr, P. (2019). Educational Leadership in the Twitterverse: Social Media, Social Networks, and the New Social Continuum. Teachers College Record, 121(14), 1-2 0. https://doi.org/10.1177/016146811912101404
  • Díez Gutiérrez, E. J., Verdeja Muñiz, M., Sarrión Andaluz, J., Buendía, L., & Macías Tovar, J. (2022). Discurso Político De Odio De La Ultraderecha Desde Twitter en Iberoamérica. Comunicar: Revista Científica Iberoamericana De Comunicación Y Educación, 30(72), 101-113. https://doi.org/10.3916/C72-2022-08
  • Fernández Navas, M., Postigo Fuentes, A. Y., Pérez Granados, L., & Alcaraz Salarirche, N. (2022). Cómo Hacer Investigación Cualitativa en El Área De Tecnología Educativa. RiiTE Revista Interuniversitaria de Investigación en Tecnología Educativa, 9 3 -116. https://doi.org/10.6018/riite.547251
  • Fischer, C., Fishman, B., & Schoenebeck, S. Y. (2019). New Contexts for Professional Learning: Analyzing High School Science Teachers’ Engagement on Twitter. Aera Open, 5(4), 1–20. https://doi.org/10.1177/2332858419894252
  • Flick, U. (2004). Introducción a La Investigación Cualitativa. Morata. https://go.revistacomunicar.com/aYt61o
  • Gao, F., & Li, L. (2017). Examining a One‐hour Synchronous Chat in a Microblogging‐based Professional Development Community. British Journal of Educational Technology, 48( 2), 332 -3 47. https://doi.org/10.1111/bjet.12384
  • García, P. G. (2022). Las Redes Sociales en La Investigación Social. Miscelánea Comillas. Revista de Ciencias Humanas y Sociales, 80(157), 407-428. https://doi.org/10.14422/mis.v80.i157.y2022.009
  • Gee, J. P. (Ed.). (2004). Situated Language and Learning: a Critique of Traditional Schooling. Psychology Press. https://doi.org/10.4324/9780203594216
  • Gee, J. P. (2017). Affinity Spaces and 21st Century Learning. Educational Technology, 57( 2), 2 7-31. https://go.revistacomunicar.com/U71Ehb
  • Gende, I. M. (2023). Aprendizaje informal en redes: Twitter y las #CharlasEducativas. Ediciones Octaedro. https://doi.org/10.36006/16414
  • Gomez, M., & Journell, W. (2017). Professionality, Preservice Teachers, and Twitter. Journal of Technology and Teacher Education, 25(4), 377- 412. https://go.revistacomunicar.com/BsCx0K
  • Greenhalgh, S. P. (2021). Differences Between Teacher-focused Twitter Hashtags and Implications for Professional Development. Italian Journal of Educational Technology, 29(1), 26 - 45. https://doi.org/10.17471/2499-4324/1161
  • Greenhalgh, S. P., Staudt Willet, K. B., Rosenberg, J. M., & Koehler, M. J. (2018). Tweet, and We Shall Find: Using Digital Methods to Locate Participants in Educational Hashtags. TechTrends, 62(5), 501-508. https://doi.org/10.1007/s11528-018-0313-6
  • Greenhow, C., & Lewin, C. (2016). Social Media and Education: Reconceptualizing the Boundaries of Formal and Informal Learning. Learning, Media and Technology, 41(1), 6 -3 0. https://doi.org/10.1080/17439884.2015.1064954
  • Greenhow, C., Staudt Willet, K. B., & Galvin, S. (2021). Inquiring Tweets Want to Know:# Edchat Supports for# Remoteteaching During Covid‐19. British Journal of Educational Technology, 52(4), 14 34-1454. https://doi.org/10.1111/bjet.13097
  • Heller, M. (2005). Discourse and Interaction. In The handbook of discourse analysis (pp. 250-264). Wiley. https://doi.org/10.1002/9780470753460
  • Kadushin, C. (2012). Understanding Social Networks. Oxford University Press. https://bit.ly/473Q8w5
  • Konikoff, D. (2021). Gatekeepers of Toxicity: Reconceptualizing Twitter’s Abuse and Hate Speech Policies. Policy & Internet, 13(4), 502-521. https://doi.org/10.1002/poi3.265
  • Li, G., & Liu, F. (2014). Sentiment Analysis Based on Clustering: a Framework in Improving Accuracy and Recognizing Neutral Opinions. Applied Intelligence, 40(3), 441-452. https://doi.org/10.1007/s10489-013-0463-3
  • Luo, T., Freeman, C., & Stefaniak, J. (2020). “Like, comment, and share”—professional development through social media in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1659-1683. https://doi.org/10.1007/s11423-020-09790-5
  • Marcelo-Martínez, P., & Marcelo, C. (2022). Espacios de afinidad docente en Twitter: El caso del hashtag #Claustrovirtual. Revista de Educación a Distancia (RED), 22(70), 1-30. https://doi.org/10.6018/red.510951
  • Marcelo, C., & Marcelo, P. (2021). Educational Inf luencers on Twitter. Analysis of Hashtags and Relationship Structure. Comunicar, 29(69), 73-83. https://doi.org/10.3916/C68-2021-06
  • Maxwell, J. A. (2012). Qualitative Research Design:An Interactive Approach. Sage Publications. https://go.revistacomunicar.com/NUpyhu
  • Miller, E. M., Jolly, J. L., Latz, J. N., & Listman, K. (2022). Inf luencers and Major Themes in a Gifted Education Community of Practice on Twitter. Journal of Advanced Academics, 33(3), 469-504. https://doi.org/10.1177/1932202X221099590
  • Moreno-Fernández, O., & Gómez-Camacho, A. (2023). Impact of the Covid-19 Pandemic on Teacher Tweeting in Spain: Needs, Interests, and Emotional Implications. Educación XX1, 26(2), 185-208. https://doi.org/10.5944/educxx1.34597
  • Prestridge, S. (2019). Categorising Teachers’ Use of Social Media for Their Professional Learning: a Self-generating Professional Learning Paradigm. Computers & Education, 129, 14 3 -158. https://doi.org/10.1016/j.compedu.2018.11.003
  • Rosenberg, J. M., Greenhalgh, S. P., Koehler, M. J., Hamilton, E. R., & Akcaoglu, M. (2016). An Investigation of State Educational Twitter Hashtags (Seths) as Affinity Spaces. E-learning and Digital Media, 13(1-2), 24- 44. https://doi.org/10.1177/2042753016672351
  • Sangrà Morer, A., & Wheeler, S. (2013). Nuevas formas de aprendizaje informales: ¿o estamos formalizando lo informal? RUSC, Universities & Knowledge Society, 10(1), 28 6 -293. https://doi.org/10.7238/rusc.v10i1.1689
  • Shea, D., Alemu, D. S., & Visser, M. J. (2020). A Social Network Study of Transformational Teacher Inf luence. Teacher Development, 24(5), 603-625. https://doi.org/10.1080/13664530.2020.1818614
  • Singh, L. (2020). A Systematic Review of Higher Education Academics’ Use of Microblogging for Professional Development: Case of Twitter. Open Education Studies, 2(1), 6 6 - 81. https://doi.org/10.1515/edu-2020-0102
  • Stake, R. F. (2010). Investigación De Estudios De Casos. Morata. https://bit.ly/3ObAHco
  • Tracy, S. (2021). Calidad Cualitativa: Ocho Pilares Para Una Investigación Cualitativa De Calidad. Márgenes Revista De Educación De La Universidad De Málaga, 2(2), 173 -2 01. https://doi.org/10.24310/mgnmar.v2i2.12937
  • Visser, R. D., Evering, L. C., & Barrett, D. E. (2014). #TwitterforTeachers: The Implications of Twitter as a Self-Directed Professional Development Tool for K–12 Teachers. Journal of Research on Technology in Education, 46(4), 396-413. https://doi.org/10.10 8 0/15391523.2014.925694
  • Wagh, R., & Punde, P. (2018). Survey on Sentiment Analysis Using Twitter Dataset. In 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 208-211). IEEE. https://doi.org/10.1109/ICECA.2018.8474783
  • Wagner, C. J., & González-Howard, M. (2018). Studying Discourse as Social Interaction: the Potential of Social Network Analysis for Discourse Studies. Educational Researcher, 47(6), 375-383. https://doi.org/10.3102/0013189X18777741
  • Wojcik, S., & Hughes, A. (2019). Sizing Up Twitter Users. Pew Research Center. https://go.revistacomunicar.com/HL0roj
  • Wu, Q., Qi, X., Fuller, E., & Zhang, C.-Q. (2013). “Follow the Leader”: a Centrality Guided Clustering and Its Application to Social Network Analysis. The Scientific World Journal, 2013, 368568 https://doi.org/10.1155/2013/368568