Archived Social Media Data as a Research Resource

Öz

Social media is used today in numerous contexts, from government institutions to media organizations and from the private sector to academic research, as well as by individuals. The use of social media across a wide range of fields generates valuable new data that researchers can use in their studies. This so-called “social media data” represents an unprecedented research resource. The emergence of Application Programming Interfaces (APIs) and the shaping of social media platforms around them have led researchers to use platform APIs as a highly effective way to collect and archive social media data. Few studies exist on social media data, the value of which has only recently been recognized in the field of information and records management. This paper emphasizes the importance of social media data collected and archived through social media platform APIs as a new source for research. It also highlights areas of academic research where these data are currently used. Furthermore, the paper explains the concepts of big data and data mining in the context of social media. A literature-based qualitative research method was used to obtain data for the study, and these data were analyzed through the document analysis technique.

Anahtar Kelimeler

• Social media
• social media data
• API
• data source
• social media research

Bir Araştırma Kaynağı Olarak Arşivlenen Sosyal Medya Verilerinin Kullanımı

Öz

Günümüzde sosyal medya, bireysel olarak kullanımının yanında devlet kurumlarından medya kuruluşlarına, özel sektörden akademik araştırmalara kadar bir dizi alanda kullanılmaktadır. Sosyal medyanın bu çok sayıda alanda kullanımı ile birlikte, araştırmacıların çalışmalarında kullanabilecekleri değerli yeni veriler ortaya çıkmaktadır. “Sosyal medya verileri” olarak adlandırılan bu değerli veri türü daha önce görülmemiş bir nitelikte bir araştırma kaynağı yaratmıştır. Uygulama Programlama Arayüzlerinin (Application Programming Interface, API) ortaya çıkması ve sosyal medya platformlarının API’ler etrafında şekillenmesi, araştırmacıları sosyal medya platformlarından veri toplamanın ve verileri arşivlemenin en etkili yollarından biri olarak platform API’lerini kullanmaya yöneltmiştir. Bilgi ve belge yönetimi alanında değeri yeni fark edilen sosyal medya verileri üzerine pek fazla çalışma bulunmamaktadır. Bu çalışmada; sosyal medya verileri kavramı ile sosyal medya platformlarının API’leri aracılığıyla toplanıp arşivlenen sosyal medya verilerinin araştırmalarda yeni bir kaynak türü olarak önemine vurgu yapılmış, bu verilerin hâlihazırda kullanıldığı akademik araştırma alanlarına işaret edilmiştir. Çalışma kapsamında ayrıca sosyal medya büyük verisi ve sosyal medya veri madenciliği kavramları da açıklanmıştır. Literatüre dayalı nitel araştırma yönteminin kullanıldığı çalışmada elde edilen verilerin analizi için de doküman analizi tekniğinden yararlanılmıştır

Anahtar Kelimeler

• Sosyal medya
• sosyal medya verisi
• API
• veri kaynağı
• sosyal medya araştırması

Kaynakça

1. Acker, A. ve Kriesberg, A. (2017). Tweets may be archived: Civic engagement, digital preservation and Obama White House social media data. Proceedings of the Association for Information Science and Technology, 54(1), 1-9. https://doi.org/10.1002/pra2.2017.14505401001 google scholar
2. Aggarwal, C. C. (2011). An introduction to social network data analytics. In C. Aggarwal (Ed.), Social Network Data Analytics (pp. 1-15). Boston, USA: Springer. https://doi.org/10.1007/978-1-4419-8462-3_1 google scholar
3. Aggarwal, P. (2019). Classification approaches to identify informative tweets. In Proceedings Of The Student Research Workshop Associated with RANLP 2019 (pp. 7-15). Bulgaria: Varna. doi:10.26615/issn.2603-2821.2019_002 google scholar
4. Al-Hajjar, D., Jaafar, N., Al-Jadaan, M. ve Alnutaifi, R. (2015). Framework for social media big data quality analysis. In N. Bassiliades et al. (Eds.), New Trends in Database and Information Systems II (pp. 301-314). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-10518-5_23 google scholar
5. Arshad, H., Jantan, A. ve Omolara, E. (2019). Evidence collection and forensics on social networks: research challenges and directions. Digital Investigation, 28, 126-138. https://doi.org/10.1016/j.diin.2019.02.001 google scholar
6. Ashok, A., Guruprasad, M., Prakash, C. O. ve Shylaja, S. S. (2019). A Machine learning approach for disease surveillance and visualization using Twitter data. In 2019 International Conference on Computational Intelligence in Data Science (ICCIDS) (pp. 1-6). doi:10.1109/ICCIDS.2019.8862087 google scholar
7. Batrinca, B. ve Treleaven, P. C. (2015). Social media analytics: a survey of techniques, tools and platforms. AI & SOCIETY, 30(1), 89-116. https://doi.org/10.1007/s00146-014-0549-4 google scholar
8. Beguerisse Diaz, M. (2016). Study of dynamic communities on networks, diabetes tweets 2013-2014 [Data collection]. UK Data Service. http://doi.org/10.5255/UKDA-SN-852474 google scholar

9. Beninger, K., Fry, A., Jago, N., Lepps, H., Nass, L., Silvester, H., ... Silvester, H. (2014). Researchusingsocial media; users’ views. NatCen Social Research. Retrieved from http://www.natcen.ac.uk/media/282288/">http://www.natcen.ac.uk/media/282288/ p0639-research-using-social-media-report-final-190214.pdf%5Cnhttp://www.natcen.ac.uk google scholar
10. Birch, S., Ounis, I., Macdonald, C. ve Yang, X. (2019). Electoral violence incident dataset 2015-2016 [Data collection]. UK Data Service. http://doi.org/10.5255/UKDA-SN-853262 google scholar
11. Bishop, E. L., Hagen, S., Koscı'k, M., Vavra, M., Stebe, J., Ryan, L., ... R0d, L.-M. (2019). Report on legal and ethical framework and strategies related to access, use, re-use, dissemination and preservation of social media data. SERISS (Synergies for Europe’s Research Infrastructures in the Social Sciences) (C. 6.3). Retrieved from https://seriss.eu/wp- content/uploads/2019/11/D6.3-Report-on-legal-and-ethical-framework-and-strategies...__FINAL.pdf google scholar
12. Boyd, D. ve Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information Communication and Society, 15(5), 662-679. https://doi. org/10.1080/1369118X.2012.678878 google scholar
13. Brangbour, E., Bruneau, P., Marchand-Maillet, S., Hostache, R., Chini, M., Matgen, P. ve Tamisier, T. (2019). Computing flood probabilities using Twitter: Application to the Houston urban area during Harvey. In J. Brajard, A. Charantonis, C. Chen ve J. Runge (Eds.), 9th International Workshop on Climate Informatic (pp. 22-26). Boulder, USA: National Center for Atmospheric Research. Retrieved from https://opensky. ucar.edu/islandora/object/technotes%3A581/datastream/PDF/view google scholar
14. Bruns, A. ve Burgess, J. (2016). Methodological innovation in precarious spaces: the case of Twitter. In H. Snee, C. Hine, Y. Morey, S. Roberts ve H. Watson (Eds.), Digital methods for social science: an interdisciplinary guide to research innovation (pp. 17-33). London, UK: Palgrave Macmillan. https:// doi.org/10.1057/9781137453662_2 google scholar
15. Bruns, A., Burgess, J., Crawford, K. ve Shaw, F. (2012). \#qldfloods and @QPSMedia: crisis communication on Twitter in the 2011 South East Queensland floods - research report. Brisbane, Australia: ARC Centre of Excellence for Creative Industries and Innovation. Retrieved from https://eprints.qut.edu.au/48241/ google scholar
16. Caplan, M. A. ve Purser, G. (2019). Qualitative inquiry using social media: a field-tested example. Qualitative Social Work, 18(3), 417-435. https://doi.org/10.1177/1473325017725802 google scholar
17. Croeser, S. ve Highfield, T. (2019). Blended data: Critiquing and complementing social media datasets, big and small. In J. Hunsinger, M. M. Allen ve L. Klastrup (Eds.), Second international handbook of internet research (pp. 669-690). Dordrecht, Netherlands: Springer. https://doi.org/10.1007/978-94-024-1555-1_15 google scholar
18. Çelik, U. (2018). Sosyal medya platformlarında veri madenciliği. H. Yıldız (Ed.), Sosyal Medyanın İş Yaşamındaki Yeri (ss. 451-471) içinde. İstanbul: Beta Yayıncılık. google scholar
19. Chen, E., Chang, H., Rao, A., Lerman, K., Cowan, G. ve Ferrara, E. (2021). COVID-19 misinformation and the 2020 U.S. presidential election. Harvard Kennedy School Misinformation Review 1, 1-17. https://doi. org/10.37016/mr-2020-57 google scholar
20. Chen, E., Deb, A. ve Ferrara, E. (2021). #Election2020: The first public Twitter dataset on the 2020 US Presidential election. Journal of Computational Social Science. https://doi.org/10.1007/s42001-021-00117-9 google scholar
21. Chukwuemeka, D. ve Abdul, A. (2017). The UK 2015 General Election, Twitter data [Data collection]. UK Data Service. http://doi.org/10.5255/UKDA-SN-852772 google scholar
22. Colombo, G. B., Burnap, P., Hodorog, A. ve Scourfield, J. (2016). Analysing the connectivity and communication of suicidal users on Twitter. Computer Communications, 73, 291-300. https://doi.org/10.1016/j. comcom.2015.07.018 google scholar
23. Cresci, S., Tesconi, M., Cimino, A. ve Dell’Orletta, F. (2015). A Linguistically-driven approach to cross-event damage assessment of natural disasters from social media messages. In A. Gangemi, S. Leonardi ve A. Panconesi (Eds.), Proceedings of the 24th International Conference on World Wide Web (pp. 1195-1200). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/2740908.2741722 google scholar
24. Data Mining VS Data Extraction: What’s the Difference? . (2021). Retrieved from https://www.octoparse. com/blog/data-mining-vs-data-extraction-whats-the-difference google scholar
25. Derczynski, L., Yang, B. ve Jensen, C. (2013). Towards context-aware search and analysis on social media data. In G. Guerrini (Eds.), ACM International Conference Proceeding Series (pp. 137-142). https://doi. org/10.1145/2452376.2452393 google scholar
26. Edwards, P., Markovic, M., Petrunova, N., Lin, C. ve Corsar, D. (2018). Tweets used to explore causes of self-reported foodborne illnesses on social media 2017 [Data collection]. UK Data Service. http://doi. org/10.5255/UKDA-SN-853375 google scholar
27. ElAlfy, A., Darwish, K. M. ve Weber, O. (2020). Corporations and sustainable development goals communication on social media: Corporate social responsibility or just another buzzword? Sustainable Development, 28(5), 1418-1430. https://doi.org/10.1002/sd.2095 google scholar
28. Ertam, F. (2017). Sosyal medya verileri için etkili bir sınıflandırma yaklaşımı. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 29(2), 67-73. https://dergipark.org.tr/tr/pub/fumbd/339547 adresinden erişildi. google scholar
29. ESOMAR. (2011). Guideline on Social Media Research. Retrieved from https://www.esomar.org/uploads/ public/knowledge-and-standards/codes-and- guidelines/ESOMAR_Guideline-for-online-research.pdf google scholar
30. Fondren, E. ve McCune, M. M. (2018). Archiving and preserving social media at the Library of Congress: Institutional and cultural challenges to build a Twitter archive. Preservation, Digital Technology and Culture, 47(2), 33-44. https://doi.org/10.1515/pdtc-2018-0011 google scholar
31. Ghani, N. A., Hamid, S., Targio Hashem, I. A. ve Ahmed, E. (2019). Social media big data analytics: A survey. Computers in Human Behavior, 101, 417-428. https://doi.org/10.1016/j.chb.2018.08.039 google scholar
32. Gökkurt Demırtel, Ö. ve Demirtel, H. (2016). Sosyal medyada kurumsal arşivleme sorunu. T. Çakmak ve N. Özel (Ed.), Uluslararası Kültürel Mirasın ve Kültürel Bellek Kurumlarının Yönetimi Kongresi (ss. 226234) içinde. Ankara: Üniversite ve Araştırma Kütüphanecileri Derneği. google scholar
33. Gundecha, P. ve Liu, H. (2012). Mining social media: A brief introduction. TutORials in Operations Research (pp. 1-17). https://doi.org/10.1287/educ.1120.0105 google scholar
34. Gürsakal, N. (2009). Sosyal ağ analizi: Pajek Ucinet ve Gmine uygulamalı. Bursa: Dora Yayıncılık. google scholar
35. Hegazi, M. O., Al-Dossari, Y., Al-Yahy, A., Al-Sumari, A. ve Hilal, A. (2021). Preprocessing Arabic text on social media. Heliyon, 7(2), 1-15. https://doi.org/10.1016/j.heliyon.2021.e06191 google scholar
36. Hemphill, L., Hedstrom, M. L. ve Leonard, S. H. (2020). Saving social media data: Understanding data management practices among social media researchers and their implications for archives. Journal of the Association for Information Science and Technology, 72(1), 97-109. https://doi.org/10.1002/ asi.24368 google scholar
37. Highfield, T. ve Leaver, T. (2014). A methodology for mapping Instagram hashtags. First Monday, 20(1). https://doi.org/10.5210/fm.v20i1.5563 google scholar
38. Huang, Q. ve Xu, C. (2014). A data-driven framework for archiving and exploring social media data. Annals of GIS, 20(4), 265-277. https://doi.org/10.1080/19475683.2014.942697 google scholar
39. Joshi, A., Sparks, R., Karimi, S., Yan, S.-L. J., Chughtai, A. A., Paris, C. ve MacIntyre, C. R. (2020). Automated monitoring of tweets for early detection of the 2014 Ebola epidemic. PLOS ONE, 15(3), e0230322. Erişim adresi: https://doi.org/10.1371/journal.pone.0230322 google scholar
40. Kaczmirek, L., Mayr, P., Vatrapu, R., Bleier, A., Blumenberg, M., Gummer, T., ... Wolf, C. (2013). Social media monitoring of the campaigns for the 2013 German Bundestag elections on Facebook and Twitter. Köln. Retrieved from https://www.gesis.org/fileadmin/upload/forschung/publikationen/gesis_reihen/ gesis_arbeitsberichte/WorkingPapers_2014-31.pdf google scholar
41. Kaplan, A. M. ve Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59-68. https://doi.Org/10.1016/j.bushor.2009.09.003 google scholar
42. Kapoor, K. K., Tamilmani, K., Rana, N. P., Patil, P., Dwivedi, Y. K. ve Nerur, S. (2018). Advances in social media research: Past, present and future. Information Systems Frontiers, 20(3), 531- 558. https://doi. org/10.1007/s10796-017-9810-y google scholar
43. Kavanaugh, A., Song, Z., Li, L. ve Fox, E. (2019). Communication behavior in an emerging democracy. In Y. Chen, F. Salem ve A. Zuiderwijk (Eds.), Proceedings of the 20th Annual International Conference on Digital Government Research (pp. 445-455). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/3325112.3325263 google scholar
44. Kavoura, A. (2014). Social media, online imagined communities and communication research. Library Review, 63(6/7), 490-504. https://doi.org/10.1108/LR-06-2014-0076 google scholar
45. Kerchner, D. ve Wrubel, L. (2020). Coronavirus tweet ids. Harvard Dataverse. https://doi.org/10.7910/DVN/ LW0BTB google scholar
46. Kinder-Kurlanda, K. (2019). Privatheitsschutz durch open data und tusted third parties: pladoyer für die öffentliche kontrolle sozialer daten. In C. Ochs, M. Friedewald, T. Hess ve J. Lamla (Eds.), Die Zukunft der datenökonomie: zwischen geschaftsmodell, kollektivgut und verbraucherschutz (pp. 103-116). Wiesbaden, Germany: Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-27511-2_6 google scholar
47. Kinder-Kurlanda, K., Weller, K., Zenk-Möltgen, W., Pfeffer, J. ve Morstatter, F. (2017). Archiving information from geotagged tweets to promote reproducibility and comparability in social media research. Big Data & Society, 4(2), 1-14. https://doi.org/10.1177/2053951717736336. google scholar
48. KVTKN, P. ve Ramakrishnudu, T. (2021). A novel method for detecting psychological stress at tweet level using neighborhood tweets. Journal of King Saud University - Computer and Information Sciences. https:// doi.org/10.1016/j.jksuci.2021.08.015 google scholar
49. Lafferty, N. T. ve Manca, A. (2015). Perspectives on social media in and as research: A synthetic review. International Review of Psychiatry, 27(2), 85-96. https://doi.org/10.3109/09540261.2015.1009419 google scholar
50. Larson, E. (2020). Big questions: Digital preservation of big data in government. The American Archivist, 83(1), 5-20. https://doi.org/10.17723/0360-9081-83.1.5 google scholar
51. Littman, J. (2017). Hurricanes Harvey and Irma tweet ids. Harvard Dataverse. https://doi.org/10.7910/DVN/ QRKIBW google scholar
52. Liu, C., Xia, S. ve Lang, C. (2021). Clothing consumption during the COVID-19 Pandemic: Evidence from mining tweets. Clothing and Textiles Research Journal, 39(4), 314-330. https://doi.org/10.1177/0887302X211014973 google scholar
53. Liu, X., Shin, H. ve Burns, A. C. (2021). Examining the impact of luxury brand’s social media marketing on customer engagement: using big data analytics and natural language processing. Journal of Business Research, 125, 815-826. https://doi.org/10.1016/j.jbusres.2019.04.042 google scholar
54. Lomborg, S. ve Bechmann, A. (2014). Using APIs for data collection on social media. The Information Society, 30(4), 256-265. https://doi.org/10.1080/01972243.2014.915276 google scholar
55. Lynn, T., Healy, P., Kilroy, S., Hunt, G., van der Werff, L., Venkatagiri, S. ve Morrison, J. (2015). Towards a general research framework for social media research using big data. In J. Kaye ve A. Druin (Eds.), 2015 IEEE International Professional Communication Conference, IPCC 2015, Limerick, Ireland, July 12-15, 2015 (pp. 1-8). https://doi.org/10.1109/ipcc.2015.7235843 google scholar
56. Mahoney, J., Feltwell, T., Ajuruchi, O. ve Lawson, S. (2016). Constructing the visual online political self: An analysis of Instagram use by the Scottish electorate. In CHI’16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 3339-3351). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/2858036.2858160 google scholar
57. Manovich, L. (2012). Trending: The promises and the challenges of big social data. In M. K. Gold (Ed.), Debates in the digital humanities (pp. 460-475). Minnesota, USA: University of Minnesota Press. Erişim adresi: http://www.jstor.org/stable/10.5749/j.ctttv8hq.30 google scholar
58. Masood, Z., Peterson, H. ve Voleti, S. (y.y.) The sentiment of U.S. Presidential Elections on Twitter. Retrieved from https://dsc-capstone.github.io/projects-2020- 2021/reports/project_1.pdf google scholar
59. Merrill, S., Sumartojo, S., Stephens, A. C. ve Coward, M. (2020). Togetherness after terror: The more or less digital commemorative public atmospheres of the Manchester Arena bombing’s first anniversary. Environment and Planning D: Society and Space, 38(3), 546-566. https://doi.org/10.1177/0263775819901146 google scholar
60. Morstatter, F., Lubold, N., Pon-Barry, H., Pfeffer, J. ve Liu, H. (2014). Finding eyewitness tweets during crises. In Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science (pp. 23-27). Baltimore, USA: Association for Computational Linguistics. doi:10.3115/v1/W14-2509 google scholar
61. Nazeer Chaudhry, H., Javed, Y., Kulsoom, F., Mehmood, Z., Iqbal Khan, Z., Shoaib, U., ... Abualigah, L. (2021). Sentiment analysis of before and after elections: Twitter data of U.S. election 2020. Electronics, 10(17), 1-26. https://doi.org/10.3390/electronics10172082 google scholar
62. Pennington, D. R. (2016). Coding of non-text data. In A. Q.-H. Luke Sloan (Eds.), The SAGE handbook of social media research methods (pp. 513-529). London: SAGE Publications. https://dx.doi. org/10.4135/9781473983847.n15 google scholar
63. Procter, R., Voss, A. ve Lvov, I. (2015). Audience research and social media data : Opportunities and challenges. Participations: Journal of Audience Reception Studies, 12(1), 470-493. Retrieved from https://core.ac.uk/ download/pdf/30319349.pdf google scholar
64. Pushpam, C. A. ve Jayanthi, J. G. (2017). Over view on data mining in social media. International Journal of Computer Sciences and Engineering, 5(11), 147-157. https://doi.org/10.26438/ijcse/v5i11.147157 google scholar
65. Qi, M. ve Edgar-Nevill, D. (2011). Social networking searching and privacy issues. Information Security Technical Report, 16(2), 74-78. https://doi.org/10.1016/j.istr.2011.09.005 google scholar
66. Rieder, B., Abdulla, R., Poell, T., Woltering, R. ve Zack, L. (2015). Data critique and analytical opportunities for very large Facebook pages: Lessons learned from exploring “We are all Khaled Said”. Big Data & Society, 2(2), 1-22. https://doi.org/10.1177/2053951715614980 google scholar
67. Saltzer, M., Stier, S., Bauerle, J., Blumenberg, M., Mechkova, V, Pemstein, D., ... Wilson, S. (2021). Twitter accounts of candidates in the German federal election 2021. GESIS Data Archive. https://doi. org/10.4232/1.13790 google scholar
68. Sanders, J. G., Tosi, A., Obradovic, S., Miligi, I. ve Delaney, L. (2021). Lessons from the UK’s lockdown: Discourse on behavioural science in times of COVID-19. Frontiers in Psychology, 12, 1- 24. https://doi. org/10.3389/fpsyg.2021.647348 google scholar
69. Schafer, V., Truc, G., Badouard, R., Castex, L. ve Musiani, F. (2019). Paris and Nice terrorist attacks: Exploring Twitter and web archives. Media, War & Conflict, 12(2), 153-170. https://doi.org/10.1177/1750635219839382 google scholar
70. Şeker Elmas, Ş. (2019). Sosyal medya mesajlarının veri madenciliği yöntemi ile duygu analizi (Sivas ili örneği) (Yüksek lisans tezi). Yükseköğretim Kurulu Başkanlığı Ulusal Tez Merkezi. (Tez No. 538097) google scholar
71. Sharma, S. ve Sharma, S. (2021). Analyzing the depression and suicidal tendencies of people affected by COVID-19’s lockdown using sentiment analysis on social networking websites. Journal of Statistics and Management Systems, 24(1), 115-133. https://doi.org/10.1080/09720510.2020.1833453 google scholar
72. Shneiderman, B., Preece, J. ve Pirolli, P. (2011). Realizing the value of social media requires innovative computing research. Communications of the ACM, 54(9), 34-37. https://doi.org/10.1145/1995376.1995389 google scholar
73. Simon, T., Goldberg, A., Aharonson-Daniel, L., Leykin, D. ve Adini, B. (2014). Twitter in the cross fire-the use of social media in the Westgate Mall terror attack in Kenya. PLOS ONE, 9(8). https://doi.org/10.1371/ journal.pone.0104136 google scholar
74. Şimşek, M. U. (2012). Sosyal ağlarda veri madenciliği üzerine bir uygulama (Yüksek lisans tezi). Yükseköğretim Kurulu Başkanlığı Ulusal Tez Merkezi. (Tez No. 321573) google scholar
75. Sloan, L. ve Morgan, J. (2015). Who tweets with their location? Understanding the relationship between demographic characteristics and the use of geoservices and geotagging on Twitter. PLOS ONE, 10(11), 1-15. https://doi.org/10.1371/journal.pone.0142209 google scholar
76. Sloan, L., Morgan, J., Burnap, P. ve Williams, M. (2015). Who tweets? Deriving the demographic characteristics of age, occupation and social class from Twitter user meta-data. PLOS ONE, 10(3), e0115545. https://doi. org/10.1371/journal.pone.0115545 google scholar
77. Social media archiving in regulated industries: Why it matters in 2021. (2020). Retrieved from https://jatheon. com/blog/social-media-archiving-in-regulated-industries/ google scholar
78. Social Media Research: tools, techniques and outputs. (y.y.). Retrieved from https://www.pulsarplatform.com/ what-is-social-media-research-top-tools-and-techniques/ google scholar
79. Social Media Research Group. (2016). Using social media for social research : An introduction, (May), 1-27. Retrieved from https://assets.publishing.service.gov.uk/government/uploads/ system/uploads/attachment_ data/file/524750/GSR_Social_Media_Research_Guidance_- _Using_social_media_for_social_research. pdf%0Ahttp://dera.ioe.ac.uk/26600/ google scholar
80. Steensen, S. (2018). Tweeting terror: an analysis of the Norwegian Twitter-sphere during and in the aftermath of the 22 July 2011 terrorist attack. In H. Hornmen ve K. Backholm (Eds.), Social media use in crisis and risk communication (pp. 15-41). Bingley, UK: Emerald Publishing Limited. https://doi.org/10.1108/978-1-78756-269-120181006 google scholar
81. Stieglitz, S., Mirbabaie, M., Ross, B. ve Neuberger, C. (2018). Social media analytics-challenges in topic discovery, data collection, and data preparation. International Journal of Information Management, 39, 156-168. https://doi.org/10.1016/j.ijinfomgt.2017.12.002 google scholar
82. Strategies for managing social media information. (y.y.). Retrieved from https://www.records.nsw.gov.au/ recordkeeping/advice/strategies-for-managing-social-media- information google scholar
83. Taylor, J. ve Pagliari, C. (2018). Mining social media data: How are research sponsors and researchers addressing the ethical challenges? Research Ethics, 14(2), 1-39. https://doi.org/10.1177/1747016117738559 google scholar
84. Thomson, S. D. ve Kilbride, W. (2015). Preserving social media: The problem of access. New Review of Information Networking, 20(1-2), 261-275. https://doi.org/10.1080/13614576.2015.1114842 google scholar
85. Torres, J., Anu, V. ve Varde, A. S. (2021). Understanding the information disseminated using twitter during the COVID-19 pandemic. In 2021 IEEE International IOT, Electronics and Mechatronics Conference, (IEMTRONICS) Piscataway, USA: IEEE. doi:10.1109/IEMTRONICS52119.2021.9422523 google scholar
86. Townsend, L. ve Wallace, C. (2016). Social media research: A guide to ethics. The University of Aberdeen. Retrieved from https://www.gla.ac.uk/media/Media_487729_smxx.pdf google scholar
87. Türkiye Bilimler Akademisi. (y.y.). Türkçe bilim terimleri sözlüğü. https://terim.tuba.gov.tr/ adesinden erişildi. google scholar
88. Tufekci, Z. (2014). Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In E. Adar ve P. Resnick (Eds.), Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014 Retrieved from http://arxiv.org/abs/1403.7400 google scholar
89. van Rooyen, G. (y.y.). What social media can tell us about a city? Retrieved from https://blog.pagefreezer. com/what-social-media-can-tell-us-about-a-city google scholar
90. Vis, F. (2013). A critical reflection on big data: Considering APIs, researchers and tools as data makers. First Monday, 18(10). https://doi.org/10.5210/fm.v18i10.4878 google scholar
91. Walker, S. (2017). The complexity of collecting digital and social media data in ephemeral contexts. (Doctoral thesis). Retrieved from https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/40612/ Walker_washington_0250E_17763.pdf?sequence=1&isAllowed=y google scholar
92. Wang, S.-Y. N. ve Inbar, Y. (2021). Moral-language use by U.S. political elites. Psychological Science, 32(1), 14-26. https://doi.org/10.1177/0956797620960397 google scholar
93. Weller, K. ve Kinder-Kurlanda, K. E. (2016). A manifesto for data sharing in social media research. In W. Nejdl ve W. Hall (Eds.), WebSci’16: Proceedings of the 2016 ACM Web Science (pp. 166-172). New York, USA: Association for Computing Machinery. https://doi.org/10.1145/2908131.2908172 google scholar
94. Y e, Q., Ozbay, K., Zuo, F. ve Chen, X. (2021). Impact of social media on travel behaviors during the COVID-19 pandemic: Evidence from New York City. Transportation Research Record, 1-20. https://doi. org/10.1177/03611981211033857 google scholar
95. Y e, Y., Ye, D., Zeljak, C., Kerchner, D., He, Y., Ye, Y ;, ... Littman, J. (2017). Web-archiving Chinese social media: Final project report. Journal of East Asian Libraries, 2017(165), 1-22. Retrieved from https:// scholarsarchive.byu.edu/cgi/viewcontent.cgi?article =2701&context=jeal google scholar
96. Y oung, K. (2013). Online and internet-based technologies: Social networking. In C. J. ve B. B. Sara Price (Ed.), The SAGE handbook of digital technology research (pp. 427-442). London: SAGE Publications. https://dx.doi.org/10.4135/9781446282229 google scholar
97. Young, S. D., Rivers, C. ve Lewis, B. (2014). Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes. Preventive medicine, 63, 112-115. https://doi.org/10.1016/j. ypmed.2014.01.024 google scholar
98. Zelenkauskaite, A. ve Bucy, E. P. (2016). View of a scholarly divide: Social media, big data, and unattainable scholarship. First Monday, 21(5). Retrieved from https://firstmonday.org/article/view/6358/5511 google scholar
99. Zeller, F. (2017). Analyzing social media data and other data sources: A methodological overview. In A. Q.-H. Luke Sloan (Eds.), The SAGE Handbook Of Social Media Research Methods (pp. 386-403). https:// dx.doi.org/10.4135/9781473983847.n23 google scholar
100. Zhang, L., Hall, M. ve Bastola, D. (2018). Utilizing Twitter data for analysis of chemotherapy. International Journal of MedicalInformatics, 120, 92-100. https://doi.Org/10.1016/j.ijmedinf.2018.10.002 google scholar