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2021 | OriginalPaper | Chapter

Using Social Media Analytics to Predict Social Media Engagement Outcome for Fortune CEOs

Authors : Hitesha Yadav, Arpan K. Kar, Smita Kashiramka

Published in: Advances in Information Communication Technology and Computing

Publisher: Springer Singapore

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Abstract

Social media has been broadly adopted by corporates for communicating and networking. Social media platforms help firms in building a relationship with the outside world. The study highlights how the adoption of social media is changing the way firms connect with their stakeholders. It highlights how CEOs’ social media engagement on behalf of the firm contributes to building up firms’ reputation amongst consumers. Influencer CEOs from top Fortune 500 companies have been used for this purpose. Social media analytics has been used in this study to get relevant insights from Twitter using methods of content analytics. Mining of user-generated content and further analysis of its impact on engagement outcome of CEOs has been done using methods such as web-scraping, topic modelling, bag-of-words, and dictionary methods. The study analyses CEOs’ engagement with tweets specific to a firm’s orientation towards adopting sustainable development goals (SDG). The study reveals how SDG-related messages on the Twitter timeline of CEOs have high user engagement and helps build customer reputation.

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Literature
1.
Grover P, Kar AK, Ilavarasan PV (2019) Impact of corporate social responsibility on reputation—insights from tweets on sustainable development goals by CEOs. Int J Inf Manage 48:39–52CrossRef
2.
Hwang S (2012) The strategic use of Twitter to manage personal public relations. Public Relat Rev 38(1):159–161CrossRef
3.
Grover P, Kar AK (2018) User engagement for mobile payment service providers–introducing the social media engagement model. J Retail Consum Serv 53
4.
Hong L, Davison B (2010) Empirical study of topic modelling in Twitter. In: SOMA’10 proceedings of the first workshop on social media analytics, pp 80–88
5.
Capriotti P, Ruesja L (2018) How CEOs use Twitter: a comparative analysis of global and Latin American companies. Int J Inf Manage 39:242–248CrossRef
6.
Zhou M, Lei L, Wang J, Fan W, Wang AG (2014) Social media adoption and corporate disclosure. J Inf Syst 29(2):23–50
7.
Korhonen J, Honkasalo A, Seppälä J (2018) Circular economy: the concept and its limitations. Ecol Econ 143:37–46CrossRef
8.
9.
10.
Batrinca B, Treleaven P (2015) Social media analytics: a survey of techniques, tools and platforms. AI Soc 30:89–116CrossRef
11.
Stieglitz S, Dang-Xuan L, Bruns A, Neuberger C (2014) Social media analytics. Bus Inf Syst Eng 6(2):89–96CrossRef
12.
Baird C, Parasnis G (2011) From social media to social customer relationship management. Strategy Leadersh 39(5):30–37CrossRef
13.
King MF, Bruner GC (2000) Social desirability bias—a neglected aspect of validity testing. Psychol Mark 17(2):79–103CrossRef
14.
Arkin RM, Gabrenya WK Jr, Appelman AS, Cochran ST (1979) Self-presentation, self-monitoring, and the self-serving bias in causal attribution. Pers Soc Psychol Bull 5(1):73–76CrossRef
15.
Rathore A, Kar AK, Ilavarasan PV (2017) Social media analytics—literature review and directions for future research. Decis Anal 14(4):229–249MathSciNetCrossRef
16.
Kar AK (2015) Integrating websites with social media—an approach for group decision support. J Decis Syst 24(3):339–353CrossRef
17.
Grover P, Kar AK (2017) Big data analytics—a review on theoretical contributions and tools used in literature. Global J Flex Syst Manage 18(3):203–229CrossRef
18.
Joseph N, Kar AK, Ilavarasan V, Ganesh S (2017) Review of discussions on Internet of Things (IoT): insights from Twitter analytics. J Global Inf Manage 25(2):37–60
19.
Schwartz H, Ungar LH (2015) Data-driven content analysis of social media: a systematic overview of automated methods. Am Acad Polit Soc Sci 659:78–94CrossRef
20.
Elo S, Kaariainen M, Kanste O, Polkki T, Utriainen K, Kyngas H (2014) Qualitative content analysis—a focus on trustworthiness. SAGE Open 4(1):2158244014522633CrossRef
21.
Nunez-Mir GC, Iannone BV III, Pijanowski BC, Kong N, Fei S (2016) Automated content analysis-addressing the big literature challenges in ecology and evolution. Meth Ecol Evol 7(11):1262–1272CrossRef
22.
Elo S, Kyngäs H (2008) The qualitative content analysis process. J Adv Nurs 62(1):107–115CrossRef
23.
Wallach H (2006) Topic modelling-beyond bag-of-words. In: ICML’06 proceedings of the 23rd international conference on machine learning, pp 977–984
24.
Verschoor CC (2003) Corporate responsibility—high priority for CEOs. Strateg Finance
25.
Hopkins D, King G (2009) A method of automated nonparametric content analysis for social science. Am J Polit Sci 54:229–247CrossRef
26.
Krippendorff K (2004) Content analysis—an introduction to its methodology. Sage, Beverly Hills, CA
27.
Le Blanc D (2015) Towards integration at last? The sustainable development goals as a network of targets. Sustain Dev 23:176–187
28.
Kassarjian HH (1997) Content analysis in consumer research. J Consum Res 4(1):8–18CrossRef
Metadata
Title
Using Social Media Analytics to Predict Social Media Engagement Outcome for Fortune CEOs
Authors
Hitesha Yadav
Arpan K. Kar
Smita Kashiramka
Copyright Year
2021
Publisher
Springer Singapore
Book
Advances in Information Communication Technology and Computing

Print ISBN: 978-981-15-5420-9

Electronic ISBN: 978-981-15-5421-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5421-6_4