Tytuł artykułu
Autorzy
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
This study aims to push the boundaries of research in practical theology by applying methods from computational social science to identify the reception of holidays in online social networks in German tweets. Can we identify how people talk about holidays and especially Christian holidays on Twitter? As a subquestion, we try to find relevant information for interreligious topics, especially between Christians and Jews: Can we see how Christian holidays are related to or embedded in their Jewish counterparts? Is there an awareness of the Jewish roots of certain Christian holidays? While there is a growing awareness of these issues, there are still a number of unanswered questions. In addition to analysing and discussing these questions, we will also discuss methodological issues. First, we will discuss how computational methods fit in with common research in practical theology. Secondly, we will discuss the challenges of working with digital data beyond quantitative and qualitative research.
Rocznik
Tom
Strony
513--522
Opis fizyczny
Bibliogr. 40 poz., il., wykr.
Twórcy
autor
- Biblisch-Theologische Akademie Wiedenest, Bergneustadt, Germany
Bibliografia
- 1. A. Matamoros-Fernández and J. Farkas, “Racism, hate speech, and social media: A systematic review and critique,” Television & New Media, vol. 22, no. 2, pp. 205–224, 2021.
- 2. T. Davidson, D. Warmsley, M. Macy, and I. Weber, “Automated hate speech detection and the problem of offensive language,” in Proceedings of the international AAAI conference on web and social media, vol. 11, no. 1, 2017, pp. 512–515.
- 3. I. Kalmar, C. Stevens, and N. Worby, “Twitter, gab, and racism: The case of the soros myth,” in proceedings of the 9th International Conference on Social Media and Society, 2018, pp. 330–334.
- 4. Z. Waseem and D. Hovy, “Hateful symbols or hateful people? predictive features for hate speech detection on twitter,” in Proceedings of the NAACL student research workshop, 2016, pp. 88–93.
- 5. S. Kumar, F. Morstatter, and H. Liu, Twitter data analytics. Springer, 2014.
- 6. H. Anber, A. Salah, and A. Abd El-Aziz, “A literature review on twitter data analysis,” International Journal of Computer and Electrical Engineering, vol. 8, no. 3, p. 241, 2016.
- 7. E. Bokányi, D. Kondor, L. Dobos, T. Sebők, J. Stéger, I. Csabai, and G. Vattay, “Race, religion and the city: twitter word frequency patterns reveal dominant demographic dimensions in the united states,” Palgrave Communications, vol. 2, no. 1, pp. 1–9, 2016.
- 8. A. Karami, M. Lundy, F. Webb, and Y. K. Dwivedi, “Twitter and research: A systematic literature review through text mining,” IEEE access, vol. 8, pp. 67 698–67 717, 2020.
- 9. L. Sinnenberg, A. M. Buttenheim, K. Padrez, C. Mancheno, L. Ungar, and R. M. Merchant, “Twitter as a tool for health research: a systematic review,” American journal of public health, vol. 107, no. 1, pp. e1–e8, 2017.
- 10. N. Joseph, A. K. Kar, P. V. Ilavarasan, and S. Ganesh, “Review of discussions on internet of things (iot): insights from twitter analytics,” Journal of Global Information Management (JGIM), vol. 25, no. 2, pp. 38–51, 2017.
- 11. M. Martı́nez-Rojas, M. del Carmen Pardo-Ferreira, and J. C. Rubio-Romero, “Twitter as a tool for the management and analysis of emergency situations: A systematic literature review,” International Journal of Information Management, vol. 43, pp. 196–208, 2018.
- 12. A.-K. Jung, S. Clausen, A. S. Franzke, J. Marx et al., “‘cambridge moralica’-towards an ethical framework for social media analytics,” Australasian Journal of Information Systems, vol. 26, 2022.
- 13. A. Sulfikar, P. Kerkhof, and M. Tanis, “Tweeting for religion: How indonesian islamic fundamentalist organizations use twitter,” Journal of Media and Religion, vol. 22, no. 1, pp. 1–16, 2023.
- 14. A.-P. Cooper, E. A. Kolog, and E. Sutinen, “Exploring the use of machine learning to automate the qualitative coding of church-related tweets,” Fieldwork in Religion, vol. 14, no. 2, pp. 140–159, 2019.
- 15. S. Woodward and R. Kimmons, “Religious implications of social media in education,” Religion & Education, vol. 46, no. 2, pp. 271–293, 2019.
- 16. A.-P. Cooper, “Using geotagged twitter data to uncover hidden church populations,” in The Desecularisation of the City. Routledge, 2018, pp. 134–147.
- 17. A.-P. Cooper, “Assessing the possible relationship between the sentiment of church-related tweets and church growth,” Studies in Religion/Sciences Religieuses, vol. 46, no. 1, pp. 37–49, 2017.
- 18. M. Aeschbach and D. Lüddeckens, “Religion on twitter: Communalization in event-based hashtag discourses,” Online Heidelberg Journal of Religions on the Internet, vol. 14, pp. 108–130, 2019.
- 19. K. Crockett, D. Mclean, A. Latham, and N. Alnajran, “Cluster analysis of twitter data: A review of algorithms,” in Proceedings of the 9th International Conference on Agents and Artificial Intelligence, vol. 2. Science and Technology Publications (SCITEPRESS)/Springer Books, 2017, pp. 239–249.
- 20. S. Ahuja and G. Dubey, “Clustering and sentiment analysis on twitter data,” in 2017 2nd International Conference on Telecommunication and Networks (TEL-NET). IEEE, 2017, pp. 1–5.
- 21. E. Baralis, T. Cerquitelli, S. Chiusano, L. Grimaudo, and X. Xiao, “Analysis of twitter data using a multiple-level clustering strategy,” in Model and Data Engineering: Third International Conference, MEDI 2013, Amantea, Italy, September 25-27, 2013. Proceedings 3. Springer, 2013, pp. 13–24.
- 22. V. Gupta and R. Hewett, “Real-time tweet analytics using hybrid hashtags on twitter big data streams,” Information, vol. 11, no. 7, p. 341, 2020.
- 23. J. Pflugmacher, S. Escher, J. Reubold, and T. Strufe, “The german-speaking twitter community reference data set,” in IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2020, pp. 1172–1177.
- 24. B. Witzenberger and J. Pfeffer, “Gender dynamics of german journalists on twitter,” in 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2022, pp. 226–230.
- 25. L. Neudert, B. Kollanyi, and P. Howard, “Junk news and bots during the german parliamentary election: What are german voters sharing over twitter?” 2017.
- 26. M. J. Cumbraos-Sánchez, R. Hermoso, D. Iñiguez, J. R. Paño-Pardo, M. Á. A. Bandres, and M. P. L. Martinez, “Qualitative and quantitative evaluation of the use of twitter as a tool of antimicrobial stewardship,” International journal of medical informatics, vol. 131, p. 103955, 2019.
- 27. J. Einspänner, M. Dang-Anh, and C. Thimm, “Computer-assisted content analysis of twitter data,” 2014.
- 28. C. Salvatore, S. Biffignandi, and A. Bianchi, “Social media and twitter data quality for new social indicators,” Social indicators research, vol. 156, pp. 601–630, 2021.
- 29. I. Dongo, Y. Cardinale, A. Aguilera, F. Martinez, Y. Quintero, G. Robayo, and D. Cabeza, “A qualitative and quantitative comparison between web scraping and api methods for twitter credibility analysis,” International Journal of Web Information Systems, vol. 17, no. 6, pp. 580–606, 2021.
- 30. L. Vidal, G. Ares, L. Machı́n, and S. R. Jaeger, “Using twitter data for food-related consumer research: A case study on “what people say when tweeting about different eating situations”,” Food Quality and Preference, vol. 45, pp. 58–69, 2015.
- 31. H. Hirschmann, Korpuslinguistik: Eine Einführung. J.B. Metzler, 2019.
- 32. S. Mason and L. Singh, “Reporting and discoverability of “tweets” quoted in published scholarship: current practice and ethical implications,” Research Ethics, vol. 18, no. 2, pp. 93–113, 2022.
- 33. I. Gurevych and H. Niederlich, “Computing semantic relatedness of germanet concepts,” in Sprachtechnologie, mobile Kommunikation und linguistische Ressourcen: Proceedings of Workshop” Applications of GermaNet II” at GLDV, 2005, pp. 462–474.
- 34. Y. Feng, E. Bagheri, F. Ensan, and J. Jovanovic, “The state of the art in semantic relatedness: a framework for comparison,” The Knowledge Engineering Review, vol. 32, p. e10, 2017.
- 35. P. Ten Have, “Doing conversation analysis,” Doing Conversation Analysis, pp. 1–264, 2007.
- 36. J. Bergmann, “Das konzept der konversationsanalyse,” Text-und Gesprächslinguistik, vol. 2, pp. 919–926, 2001.
- 37. D. A. Carson and D. J. Moo, An introduction to the New Testament. Zondervan Academic, 2009.
- 38. G. Höver and S. Mosès, In Verantwortung vor der Geschichte: Besinnung auf die jüdischen Wurzeln des Christentums. Borengässer, 1999.
- 39. G. Baltes, Die verborgene Theologie der Evangelien: Die jüdischen Feste als Schlüssel zur Botschaft Jesu. Francke, 2020.
- 40. A. Gerdmar, Roots of Theological Anti-Semitism (paperback): German Biblical Interpretation and the Jews, from Herder and Semler to Kittel and Bultmann. Brill, 2008, vol. 20
Uwagi
1. Thematic Tracks Regular Papers
2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ca55af5f-aebf-4eef-b967-ee05b8556dd6