Unlocking the Insights: Data-Analytic Examination of Social Signals in Organizational Practices
Social Media Networks (SMN) can be leveraged by executives to create and sustain impressions on internal and external stakeholders, which has implications for career success. Unlike actors in traditional impression management (IM) contexts that focus on a single targeted audience, actors employing IM tactics in SMN must consider multiple audiences at the same time. While top executives might serve as firm spokespersons, they often simultaneously behave as individuals in a connected world who are concerned with their own careers. From a theoretical standpoint, we focus on the usage of IM tactics by top executives and re-examine the nature of the relationship between these tactics and career success in the context of SMN. Overall, we seek to answer the following question: How is the usage of IM tactics in SMN associated with top executives’ career success? Specifically, we aim to understand the kinds of IM tactics (among ingratiation, intimidation, self-promotion, exemplification, supplication) that are particularly effective. We apply inductive machine learning techniques on publicly available SMN posts of top executives to answer this question. While our findings suggest support for certain theoretically-proposed dimensions such as self-promotion and exemplification, one of our surprising findings is that ingratiation can be detrimental in such contexts. Keywords: social media networks, impression management, executive career success, text mining, learning algorithms
Bio of Utku Pamuksuz
Utku Pamuksuz is an Information Systems researcher with expertise in data science, business analytics, applied mathematics, and machine learning. He has taught at the University of Illinois at Urbana Champaign in the College of Business and the School of Engineering at Northwestern University. He has been an invited speaker in academic and professional seminars in Europe, Asia, and the U.S.A. in topics ranging from computational social science to predictive analytics in the areas of Management, Finance, Strategy, and Quantitative Marketing. Mr. Pamuksuz has also built and maintained strong relationships with industry leader organizations during his Ph.D. studies including: State Farm, Goldman Sachs, McKinsey & Company, Deloitte, and KPMG. He has been awarded with the State Farm Big Data Hacking Competition Award in 2015 and 2016, and the UIUC Excellence in Teaching Award in 2016. He also holds a M.Sc. in Computer Science from Northwestern University. Mr. Pamuksuz is appointed as Visiting Assistant Professor at the University of Illinois at Urbana Champaign starting from May 2017.