使用Twitter 和 Instagram 上的大数据和商业智能用以实现数字包容

 Carlos Barroso-Moreno, Complutense University of Madrid (西班牙)

 Laura Rayon-Rumayor, Complutense University of Madrid (西班牙)

 Antonio Bautista García-Vera, Complutense University of Madrid (西班牙)

https://doi.org/10.3916/C74-2023-04

关键词

社交网络分析、大数据、教育、残疾、数字包容、影响群体

摘要

社交网络可以为包容性社会做出贡献，但它们也是不对称交流和两极分化交流的空间。这需要有能力的教师来构建具有批判性的的数字公民。本文有两个目的，将“Web scraping” 和 “text analytics” 技术作为定义教学数字能力的工具，并调查在 Twitter 和 Instagram 上哪些帖子在教育、残疾和包容方面最流行。我们分析了 2021 年 10 月 13 日至 2022 年 5 月 1 日期间的 48991 个西班牙语和英语帖子，选择了其中最流行的100 个，并确定了与内容、时间和地理空间相关的情绪、性别和影响力之间的相关性。结果表明，具有经济和政治影响力的群组是最流行的，他们将利他主义传播的非营利组织或个人放在第二位；只有在一些国际日时这种趋势才会逆转。 “Bots”不会干扰强加信息，是人工智能算法掩盖了抗议和人文内容。最有影响力的人普遍存在与政治范围的机构账户相关的男性性别。最后得出的结论是，“大数据”和“商业智能”工具可以帮助教师分析相关的教育和社会问题，并在面对新的教育挑战时也可以帮助其获得集体伦理道德。

参考资料

Arcila-Calderón, C., Sánchez-Holgado, P., Quintana-Moreno, C., Amores, J., & Blanco-Herrero, D. (2022). Hate speech and social acceptance of migrants in Europe: Analysis of tweets with geolocation. [Discurso de odio y aceptación social hacia migrantes en Europa: Análisis de tuits con geolocalización]. Comunicar, 71, 21-35. https://doi.org/10.3916/C71-2022-02

Link DOI | Link Google Scholar

Awidi, I.T., Paynter, M., & Vujosevic, T. (2019). Facebook group in the learning design of a higher education course: An analysis of factors influencing positive learning experience for students. Computers & Education, 129, 106-121. https://doi.org/10.1016/j.compedu.2018.10.018

Link DOI | Link Google Scholar

Barberá, P. (2015). Birds of the same feather tweet together: Bayesian ideal point estimation using twitter data. Political Analysis, 23(1), 76-91. https://doi.org/10.1093/pan/mpu011

Link DOI | Link Google Scholar

Barberá, P., Jost J.T., Nagler, J., Tucker J.A., & Bonneau, R. (2015). Tweeting from left to right: Is online political communication more than an echo chamber? Psychological Science, 26(10), 1531-1542. https://doi.org/10.1177/0956797615594620

Link DOI | Link Google Scholar

Bautista, A. (2021). Functional resignification and technological innovation as a digital teaching competence. IEEE. Revista Iberoamericana de Tecnologías del Aprendizaje, 16(1), 93-99. https://doi.org/10.1109/RITA.2021.3052679

Link DOI | Link Google Scholar

Becker, L.T., & Gould, E.M. (2019). Microsoft power BI: Extending excel to manipulate, analyze, and visualize diverse data. Serials Review, 45(3), 184-188. https://doi.org/10.1080/00987913.2019.1644891

Link DOI | Link Google Scholar

Brady, W.J., Wills, J.A., Burkart, D., Jost, J.T., & Van-Bavel, J.J. (2019). An ideological asymmetry in the diffusion of moralized content on social media among political leaders. Journal of Experimental Psychology: General, 148(10), 1802–1813. https://doi.org/10.1037/xge0000532

Link DOI | Link Google Scholar

Brunner, M., Palmer, S., Togher, L., & Hemsley, B. (2019). 'I kind of figured it out': The views and experiences of people with traumatic brain injury in using social media-self-determination for participation and inclusion online. International Journal Language & Communication Disorders, 54(2), 221-233. https://doi.org/10.1111/1460-6984.12405

Link DOI | Link Google Scholar

Carlsson (Ed.) (2019). Understanding media and information literacy (MIL) in the digital age. A question of democracy. University of Gothenburg. https://bit.ly/3xWsCz2

Link Google Scholar

Cheng, L.C., & Tsai, S.L. (2019). Deep learning for automated sentiment analysis of social media. In F. Spezzano, W. Chen, & X. Xiao (Eds.), Proceedings of the 2019 IEEE/ACM international conference on advances in social networks analysis and mining (pp. 1001-1004). Association for Computing Machinery. https://doi.org/10.1145/3341161.3344821

Link DOI | Link Google Scholar

De-Groot, R., Kaal, L.H., & Wouter, Ph.S. (2022). The online lives of adolescents with mild or borderline intellectual disabilities in the Netherlands: Care staff knowledge and perceptions. Journal of Intellectual & Developmental Disability. https://doi.org/10.3109/13668250.2021.2004635

Link DOI | Link Google Scholar

Del-Fresno-García, M. (2014). Haciendo visible lo invisible: Visualización de la estructura de las relaciones en red en Twitter por medio del análisis de redes sociales. Profesional de la Información, 23(3), 246-252. https://doi.org/10.3145/epi.2014.may.04

Link DOI | Link Google Scholar

Del-Fresno-García, M. (2019). Desórdenes informativos: sobreexpuestos e infrainformados en la era de la posverdad. Profesional de la Información, 28(3), 1-11. https://doi.org/10.3145/epi.2019.may.02

Link DOI | Link Google Scholar

Dellwing, M. (2021). The continuities of Twitter strategies and algorithmic terror. Society for the study of symbolic interaction. Sage. https://doi.org/10.1002/symb.585

Link DOI | Link Google Scholar

Ditrendia (Ed.) (2020, July 9). Mobile en España y en el Mundo. Ditrendia Digital Marketing Trends. https://bit.ly/3MNim3j

Link Google Scholar

Grace, E., Raghavendra, P., McMillan, J., & Gunson, J. (2019). Exploring participation experiences of youth who use AAC in social media settings: Impact of an e-mentoring intervention. Augmentative and Alternative Communication, 35(2), 132-141. https://doi.org/10.1080/07434618.2018.1557250

Link DOI | Link Google Scholar

Hemsley, B., Dann, D., Palmer, S., Allan, M., & Balandin. S. (2018). Using Twitter to access the human right of communication for people who use Augmentative and Alternative Communication. International Journal of Speech-Language Pathology, 20(1) 50-58. https://doi.org/10.1080/17549507.2017.1413137

Link DOI | Link Google Scholar

Ladogina, A., Samoylenko, I., Golovina, V., Razina, N., & Petushkova, E. (2020). Communication effectiveness in social networks of leading universities. Diálogo, 43, 35-50. https://doi.org/10.18316/dialogo.v0i43.6497

Link DOI | Link Google Scholar

Liu, B. (2010). Sentiment analysis and subjectivity. In N. Indurkhya, & F.J. Damerau (Eds.), Handbook of Natural Language Processing. Chapman and Hall/CRC. https://doi.org/10.1201/9781420085938

Link DOI | Link Google Scholar

Mitchell, R. (2018). Web scraping with Python: Collecting more data from the modern web. O'Reilly Media, Inc. https://bit.ly/3zw5nOn

Link Google Scholar

Ortega-Sánchez, D., Blanch, J.P., Quintana, J.I., Cal, E., Fuente-Anuncibay, C., & Hate, R. (2021). Speech, Emotions, and Gender Identities: A Study of Social Narratives on Twitter with Trainee Teachers. International Journal of Environmental Research and Public Health, 18(8), 4055. https://doi.org/10.3390/ijerph18084055

Link DOI | Link Google Scholar

Robles, J., Guevara, J., Casas-Mas, B., & Gómez, D. (2022). When negativity is the fuel. Bots and Political Polarization in the COVID-19 debate. [Cuando la negatividad es el combustible. Bots y polarización política en el debate sobre el COVID-19]. Comunicar, 71, 63-75. https://doi.org/10.3916/C71-2022-05

Link DOI | Link Google Scholar

Tuzel, S., & Hobbs, R. (2017). The use of social media and popular culture to advance cross-cultural understanding. [El uso de las redes sociales y la cultura popular para una mejor comprensión intercultural]. Comunicar, 51, 63-72. https://doi.org/10.3916/C51-2017-06

Link DOI | Link Google Scholar

We are social (Ed.) (2021). Digital 2021. The latest insights into the ‘state of digital’. We Are Social Ltd. https://bit.ly/3POIhJV

Link Google Scholar

White, P., & Forrester-Jones, R. (2020). Valuing e-inclusion: Social media and the social networks of adolescents with intellectual disability. Journal of Intellectual Disabilities, 24(3), 381-397. https://doi.org/10.1177/1744629518821240

Link DOI | Link Google Scholar

Fundref

This work has been supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with Universidad Complutense de Madrid in the line Excellence Programme for university teaching staff, in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).

Crossmark

技术信息

收到: 29-05-2022

修订: 21-06-2022

公认: 13-07-2022

OnlineFirst: 30-10-2022

发布日期: 01-01-2023

文章修改时间: 23 天 | 期刊编号的平均时间修订 74: 40 天

文章接受时间: 45 天 | 期刊编号的平均接受时间 74: 69 天

预印本编辑时间: 172 天 | 期刊编号的平均编辑时间预印 74: 194 天

文章编辑时间: 217 天 | 期刊编号的平均编辑时间 74: 239 天

度量

这篇文章的度量

浏览次数: 47934

对摘要的解读: 45253

PDF下载: 2681

的全部指标 74

浏览次数: 540760

对摘要的解读: 499198

PDF下载: 41562

被引用