Sosyal Ağlarda Büyük Veri: Teknoloji Markaları Üzerine Bir Araştırma

Year 2020, , 201 - 240, 30.07.2020

Özgür Kılınç Ali Arıcı

https://doi.org/10.26650/CONNECTIST2020-0082

Abstract

Sosyal ağ platformları, arama motorları, çevrimiçi ve dışı alışveriş pratikleri gibi birçok ortam aracılığıyla kurumlar ve markalar hakkında çeşitli veriler oluşmaktadır. Pazarlama bağlamında büyük veri ile ilişkili ve markalar hakkında yoğun veriler içeren kavramlardan biri de marka topluluklarıdır. Sosyal ağlar, marka topluluklarına yönelik bir içerik sunduğu gibi, kurumların paydaş grupları ile ilişki inşasına yönelik bir platform niteliği de taşımaktadır. Dolayısıyla kurumların sosyal ağları, marka topluluğu oluşturma ve kurumsal iletişime yönelik içerikleri sunma açısından ilgili paydaşlar ile ilişki geliştirmede önemli platformlar arasındadır. Bu doğrultuda çalışmanın amacı Samsung, Huawei ve Xiaomi olmak üzere üç teknoloji markasının sosyal ağlarında yer alan içerikleri incelemektir. Araştırma kapsamında markaların sosyal medya kanallarını kullanım biçimlerinin daha çok pazarlama amaçlı halkla ilişkiler temelinde şekillendiği sonucuna ulaşılmıştır. İncelenen markaların, etkileşim yaratma konusunda sınırlı kaldığı, anlam yaratma becerisini, simetrik dili ve kullanıcının ürettiği içerik yaklaşımını Instagram temelinde daha sık kullandığı; Twitter platformunun marka topluluklarının ‘sosyal’ faktörlerini hayata geçirme ve trafik oluşturma konusunda daha popüler olduğu görülmüştür. Markaların paylaşımlarında ‘duygular,’ ‘marka faaliyetleri’ ve ‘marka değeri/yenilikçiliği’ temalarının daha çok öne çıktığı; teknoloji markaları arasında en popüler ve tüm markalarca kullanılan sosyal medya ortamlarının Facebook ve Twitter olduğu belirlenmiştir.

Keywords

Sosyal ağlar, büyük veri, marka toplulukları, teknoloji markaları, halkla ilişkiler

Supporting Institution

Yazarlar bu çalışma için finansal destek almadığını beyan etmiştir.

Big Data on Social Networks: A Research on Technology Brands

Abstract

Various data is generated about corporations and brands through social network platforms, search engines, online and offline shopping practices. One of the concepts associated with big data in the marketing context and containing intensive data about brands is brand communities. Social networks provide content for brand communities as well as a platform for building relationships with stakeholder groups. Thus, corporate social networks are among the important platforms in developing relationships with relevant stakeholders in terms of creating a brand community and presenting content for corporate communication. In this direction, the purpose of this study is to analyse the content on the social networks of three technology brands: Samsung, Huawei and Xiaomi. Within the scope of the research, it is concluded that the usage of social media channels of brands is shaped on the basis of marketing public relations. It was seen that brands have been limited in creating interaction and use their ability to create meaning, symmetrical language and user-generated content approach more frequently on the basis of Instagram and the Twitter platform appearing to be more popular in actualising the ‘social’ factors of brand communities and generating traffic. It was determined that the themes of ‘emotions,’ ‘brand activities’ and ‘brand value-innovation’ are more prominent in the sharing of brands and the most popular social media used by all technology brands are Facebook and Twitter.

Keywords

Social networks, big data, brand communities, technology brands, public relations

References

• Adjei, M. T., Noble, S. M., & Noble, C. H. (2010). The influence of C2C communications in online brand communities on customer purchase behavior. Journal of the Academy of Marketing Science, 38(5), 634-653.
• Andersen, P. H. (2005). Relationship marketing and brand involvement of professionals through web-enhanced brand communities: The case of Coloplast. Industrial Marketing Management, 34(3), 285-297.
• Arruda-Filho, E. J., Cabusas, J. A., & Dholakia, N. (2010). Social behavior and brand devotion among iPhone innovators. International Journal of Information Management, 30(6), 475-480.
• Arthur, L. (2013). Big Data Marketing: Engage Your Customers More Effectively and Drive Value. Hoboken, NJ: John Wiley & Sons.
• Baldus, B. J., Voorhees, C., & Calantone, R. (2015). Online brand community engagement: Scale development and validation. Journal of Business Research, 68(5), 978-985.
• Bolhari, A. (2016). Bir data from management perspective. In A. Aggarwal (Ed.), Managing big data integration in the public sector (pp. 92-106). USA: IGI Global.
• Bowler, Jr, G. M. (2010). Netnography: A method specifically designed to study cultures and communities online. The Qualitative Report, 15(5), 1270-1275.
• boyd, d., & Crawford, K. (2011). Six provocations for big data. a decade in Internet time: Symposium on the dynamics of the Internet and society. http://dx.doi.org/10.2139/ssrn.1926431
• Bughin, J., Chui, M., & J. Manyika (2010). Clouds, big data and smart assets: Ten tech-enabled business trends to watch. McKinsey Quarterly, 4, 26-43.
• Burgess, J. (2012). The iPhone moment, the Apple Brand and the creative consumer: From “hackability and usability” to cultural generativity. In L. Hjorth, J. Burgess, & I. Richardson (Eds.), Studying Mobile Media: Cultural Technologies, Mobile Communication, and the iPhone (pp. 28-42). New York, USA: Routledge.
• Canalys, (2018). Newsroom. Retrieved from https://www.canalys.com/newsroom/apple-ships-717m-smartphones-in-q4-2018-as-global-market-falls-6
• Carah, N., & Shaul, M. (2015). Brands and Instagram: Point, tap, swipe, glance. Mobile Media & Communication, 4(1), 69-84.
• Chan, C. L., Ho, A. H., Leung, P. P., Chochinov, H. M., Neimeyer, R. A., Pang, S. M., & Tse, D. M. (2012). The blessings and the curses of filial piety on dignity at the end of life: Lived experience of Hong Kong Chinese adult children caregivers. Journal of Ethnic and Cultural Diversity in Social Work, 21(4), 277-296.
• Cova, B., & Cova, V. (2001). Tribal aspects of postmodern consumption research: The case of French in-line skaters. Journal of Consumer Behaviour, 1(1), 67-76.
• Cova, B., & Cova, V. (2002). Tribal marketing: The tribalisation of society and its impact on the conduct of marketing. European Journal of Marketing, 36(5/6), 595-620.
• Drisko, J. W., & Maschi, T. (2016). Content Analysis. New York, USA: Oxford University Press.
• Duncan, T., & Moriarty, S. E. (1998). A communication-based marketing model for managing relationships. Journal of Marketing, 62(2), 1-13.
• Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107-115.
• Forman J., & Damschroder L. (2008). Qualitative content analysis. In L. Jacoby, & L. Siminoff (Eds.), Empirical Research for Bioethics: A Primer, 11, (pp. 39-62). Oxford, UK: Elsevier Publishing.
• Goggin, G. (2006). Cell Phone Culture: Mobile Technology in Everyday Life. Abingdon, Oxon: Routledge.
• Gratton, C., & Jones, I. (2010). Research Methods for Sports Studies. New York: Routledge.
• Guidry, J. P., Jin, Y., Orr, C. A., Messner, M., & Meganck, S. (2017). Ebola on Instagram and Twitter: How health organizations address the health crisis in their social media engagement. Public Relations Review, 43(3), 477-486.
• Gupta, D., & Rani, R. (2019). A study of big data evolution and research challenges. Journal of Information Science, 45(3), 322-340.
• Habibi, M. R., Laroche, M., & Richard, M. O. (2014). Brand communities based in social media: How unique are they? Evidence from two exemplary brand communities. International Journal of Information Management, 34(2), 123-132.
• Halavais, A. (2015). Bigger sociological imaginations: Framing big social data theory and methods. Information, Communication & Society, 18(5), 583-594.
• Hand, D. J. (2007). Principles of data mining. Drug-Safety, 30, 621-622.
• Hardey, M. (2014). Marketing narratives: Researching digital data, design and the in/visible consumer. In M. Hand & S. Hillyard (Eds.), Big Data? Qualitative Approaches to Digital Research Studies in Qualitative Methodology, (pp. 115-135). Bingley, UK: Emerald Group Publishing Limited.
• Hesse-Biber, S. N., & Leavy, P. (2011). The Practice of Qualitative Research. Thousand Oaks, CA: Sage.
• Hollebeek, L. D., & Chen, T. (2014). Exploring positively-versus negatively-valenced brand engagement: A conceptual model. Journal of Product & Brand Management, 23(1), 62-74.
• Holmes, D. E. (2017). Big Data: A Very Short Introduction. Oxford, UK: Oxford University Press.
• Hook, M., Baxter, S., & Kulczynski, A. (2018). Antecedents and consequences of participation in brand communities: A literature review. Journal of Brand Management, 25(4), 277-292.
• Hur, W. M., Ahn, K. H., & Kim, M. (2011). Building brand loyalty through managing brand community commitment. Management Decision, 49(7), 1194-1213.
• Jacobs, A. (2009). The pathologies of big data. Communications of the ACM, 52(8), 36-44.
• Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big data and its technical challenges. Communications of the ACM, 57(7), 86-94.
• Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013, January). Big data: Issues and challenges moving forward. In 2013 46th Hawaii International Conference on System Sciences (pp. 995-1004). IEEE.
• Kitchin, R. (2013). Big data and human geography: Opportunities, challenges and risks. Dialogues in Human Geography, 3(3), 262-267.
• Kondracki, N. L., Wellman, N. S., & Amundson, D. R. (2002). Content analysis: Review of methods and their applications in nutrition education. Journal of Nutrition Education and Behavior, 34(4), 224-230.
• Kothari, C. R. (2004). Research methodology: Methods and techniques. New Delhi, India: New Age International Publishers.
• Kozinets, R. V. (1999). E-tribalized marketing?: The strategic implications of virtual communities of consumption. European Management Journal, 17(3), 252-264.
• Kuckartz, U. (2014). Qualitative Text Analysis: A Guide to Methods, Practice and Using Software. Thousand Oaks, CA: Sage.
• Kuo, Y. F., & Feng, L. H. (2013). Relationships among community interaction characteristics, perceived benefits, community commitment, and oppositional brand loyalty in online brand communities. International Journal of Information Management, 33(6), 948-962.
• Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6, 70-73.
• Letouze, E. (2012). Big Data for development: Challenges & opportunities. UN Global Pulse, 47. Retrieved from http://www.unglobalpulse.org/projects/BigDataforDevelopment
• Lup, K., Trub, L., & Rosenthal, L. (2015). Instagram# instasad?: Exploring associations among Instagram use, depressive symptoms, negative social comparison, and strangers followed. Cyberpsychology, Behavior, and Social Networking, 18(5), 247-252. https://doi.org/10.1089/cyber.2014.0560
• Mahrt, M., & Scharkow, M. (2013). The value of big data in digital media research. Journal of Broadcasting & Electronic Media, 57(1), 20-33. https://doi.org/10.1080/08838151.2012.761700
• Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute. Retrieved from http://www.mckinsey. com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation
• Matz, S. C., & Netzer, O. (2017). Using big data as a window into consumers’ psychology. Current Opinion in Behavioral Sciences, 18, 7-12. http://dx.doi.org/10.1016/j.cobeha.2017.05.009
• Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution that Will Transform How We Live, Work, and Think. Boston, MA: Houghton Mifflin Harcourt.
• McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 59-66.
• McAlexander, J. H., Schouten, W. J., & Koening, F. H. (2002). Building brand community. Journal of Marketing, 66(1), 38-54.
• Meister, S. (2012). Brand Communities for Fast Moving Consumer Goods: An Empirical Study of Members’ Behavior and the Economic Relevance for the Marketer. Wiesbaden, Germany: Springer.
• Morabito, V. (2015). Big Data and Analytics: Strategic and Organizational Impacts. Switzerland: Springer.
• Moro, S., Rita, P., & Vala, B. (2016). Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach. Journal of Business Research, 69(9), 3341-3351.
• Muñiz, A. M. Jr., & Hamer, L. O. (2001). Us versus them: Oppositional brand loyalty and the Cola wars. Advances in Consumer Research, 28, 355-361.
• Muñiz, A. M. Jr., & O’Guinn, C. T. (2001). Brand community. Journal of Consumer Research, 27, 412-432.
• Muñiz, A. M. Jr., & Schau, H. J. (2007). Vigilante marketing and consumer-created communications. Journal of Advertising, 36(3), 35-50.
• Nagaraj, K., Sharvani, G. S., & Sridhar, A. (2018). Emerging trend of big data analytics in bioinformatics: A literature review. International Journal of Bioinformatics Research and Applications, 14(1-2), 144-205.
• Neuendorf, K. A. (2017). The Content Analysis Guidebook. Thousand Oaks, CA: Sage.
• Niño, M., & Illarramendi, A. (2015). Understanding big data: Antecedents, origin and later development. DYNA New Technologies, 2(1), 1-8.
• Nyikes Z., & Rajnai, Z. (2015). Big data, as part of the critical infrastructure. In Proceedings of the IEEE 13th International Symposium on Intelligent Systems and Informatics (SISY) - Subotica, 217-222. Owais, S. S., & Hussein, N. S. (2016). Extract five categories CPIVW from the 9V’s characteristics of the big data. International Journal of Advanced Computer Science and Applications, 7(3), 254-258.
• Papasolomou, I., & Melanthiou, Y. (2012). Social media: Marketing public relations’ new best friend. Journal of Promotion Management, 18(3), 319-328.
• Parks, M. R. (2014). Big data in communication research: Its contents and discontents. Journal of Communication, 64(2), 355-360.
• Pathak, X., & Pathak-Shelat, M. (2017). Sentiment analysis of virtual brand communities for effective tribal marketing. Journal of Research in Interactive Marketing, 11(1), 16-38.
• Piatetsky‐Shapiro, G., & Frawley, W. J. (1991). Knowledge Discovery in Databases. Cambridge, UK: AAAI/MIT Press.
• Prykop, C., & Heitmann, M. (2006). Designing mobile brand communities: Concept and empirical illustration. Journal of Organizational Computing and Electronic Commerce, 16(3-4), 301-323.
• Rafferty, W., Rafferty, L., & Hung, P. C. (2016). Introduction to big data. In P. C. K. Hung (Ed.), Big data Applications and Use Cases (pp. 1-15). Switzerland: Springer.
• Ramakrishnan, V. (2019a). 23 most followed brands on Facebook in 2019. Retrieved from https://blog.unmetric. com/most-followed-brands-facebook-2019#:~:text=Samsung%20%E2%80%93%20160%20million%20 followers,most%20followed%20brands%20on%20Facebook.
• Ramakrishnan, V. (2019b). 23 most followed brands on Twitter in 2019. Retrieved from https://blog.unmetric.com/ most-followed-brands-on-twitter
• Rheingold, H. (1993). The Virtual Community: Finding Connection in a Computerized World. Boston, MA: Longman Publishing.
• Richards, Z., Thomas, S. L., Randle, M., & Pettigrew, S. (2015). Corporate social responsibility programs of Big Food in Australia: A content analysis of industry documents. Australian and New Zealand Journal of Public Health, 39(6), 550-556.
• Rourke, L., Anderson, T., Garrison, D. R., & Archer, W. (2001). Methodological issues in the content analysis of computer conference transcripts. International Journal of Artificial Intelligence in Education, 12, 8-22.
• Russom, P. (2011). Big Data Analytics. TDWI Best Practices Report, Fourth Quarter (pp. 1-35). Retrieved from https://vivomente.com/wp-content/uploads/2016/04/big-data-analytics-white-paper.pdf
• Schöch, C. (2013). Big? Smart? Clean? Messy? Data in the humanities. Journal of Digital Humanities, 2(3), 2-13.
• Schreier, M. (2012). Qualitative Content Analysis in Practice. London, UK: Sage.
• Shen, B., & Bissell, K. (2013). Social media, social me: A content analysis of beauty companies’ use of Facebook in marketing and branding. Journal of Promotion Management, 19(5), 629-651.
• Silverman, D. (2012). Doing Qualitative Research: A Practical Handbook. Thousand Oaks, CA: Sage.
• Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 102-113.
• Stacks, D. W. (2017). Primer of Public Relations Research. New York, USA: The Guilford Press.
• Statista (2018). Number of monthly active Instagram users from January 2013 to June 2018. Retrieved from https:// www.statista.com/statistics/253577/number-of-monthly-active-instagram-users/
• Strong, C. (2015). Humanizing Big Data: Marketing at the Meeting of Data, Social Science & Consumer Insight. London, UK: Kogan Page.
• Ting, H., Ming, W. W. P., de Run, E. C., & Choo, S. L. Y. (2015). Beliefs about the use of Instagram: An exploratory study. International Journal of Business and Innovation, 2(2), 15-31.
• Vaismoradi, M., Jones, J., Turunen, H., & Snelgrove, S. (2016). Theme development in qualitative content analysis and thematic analysis. Journal of Nursing Education and Practice, 6(5), 100-110.
• Veloutsou, C., & Moutinho, L. (2009). Brand relationships through brand reputation and brand tribalism. Journal of Business Research, 62(3), 314-322.
• Wang, X., White, L., & Chen, X. (2015). Big data research for the knowledge economy: past, present, and future. Industrial Management & Data Systems, 115(9), 1566-1576.
• Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.
• Wang, Y., Kung, L., Ting, C., & Byrd, T. A. (2015, January). Beyond a technical perspective: understanding big data capabilities in health care. In 2015 48th Hawaii International Conference on System Sciences (pp. 3044-3053). IEEE.
• Wiencierz, C., & Röttger, U. (2019). Big data in public relations: A conceptual framework. Public Relations Journal, 12(3), 1-15.
• Wiesenberg, M., Zerfass, A., & Moreno, A. (2017). Big data and automation in strategic communication. International Journal of Strategic Communication, 11(2), 95-114.
• Wirtz, J., Den Ambtman, A., Bloemer, J., Horvath, C., Ramaseshan, B., Van de Klundert, J., Canli, Z. G., & Kandampully, J. (2013). Managing brands and customer engagement in online brand communities. Journal of Service Management, 24(3), 223-244.
• Wong, X. L., Liu, R. C., & Sebaratnam, D. F. (2019). Evolving role of Instagram in #medicine. Internal Medicine Journal, 49(10), 1329-1332.
• Wu, M. Y., & Pearce, P. L. (2014). Appraising netnography: Towards insights about new markets in the digital tourist era. Current Issues in Tourism, 17(5), 463-474.
• Yan, J. (2011). Social media in branding: Fulfilling a need. Journal of Brand Management, 18(9), 688-696.
• Zhang, Y., & Cole, S. T. (2016). Dimensions of lodging guest satisfaction among guests with mobility challenges: A mixed-method analysis of web-based texts. Tourism Management, 53, 13-27.
• Zhang, Y., & Wildemuth, B. M. (2017). Qualitative analysis of content. In B. M. Wildemuth (Ed.), Applications of social research methods to questions in information and library science, (pp. 318-329). Santa Barbara, CA: Libraries Unlimited.