Let’s play on Facebook: using sentiment analysis and social media metrics to measure the success of YouTube gamers’ post types

This paper discusses the analysis results of successful self-marketing techniques on Facebook pages in the cases of three YouTube gamers: PewDiePie, Markiplier, and Kwebbelkop. The research focus was to identify significant differences in terms of the gamers’ user-generated Facebook metrics and commentary sentiments. Analysis of variance (ANOVA) and k-nearest neighbor sentiment analysis were employed as core research methods. ANOVA of the classified post categories revealed that photos tended to show significantly more user-generated interactions than other post types, while, on the other hand, re-posted YouTube videos gained significantly fewer numbers in the retrieved metrics than other content types. K-nearest neighbor sentiment analysis pointed out underlying follower negativity in cases where user-generated activity was relatively low, thereby improving the understanding of the opinion of the masses previously hidden behind metrics such as the number of likes, comments, and shares. The paper at hand highlights the methodological design of the study as well as a detailed discussion of key findings and their implications, and future work. The results per se indicate the need to utilize natural language processing techniques to optimize brand communication on social media and highlight the importance of considering machine learning sentiment analysis techniques for a better understanding of consumer feedback.(c) The Author(s) 201

An investigation of salespeople’s nonverbal behaviors and their effect on charismatic appearance and favorable consumer responses

The concept of charisma has gained considerable interest among social scientists in multiple disciplines. Nevertheless, research on charisma in the marketing field is scarce, and little is known about which specific nonverbal behaviors predict perceived charisma and lead to positive consumer responses. Therefore, the aim of this article is to identify nonverbal behaviors that lead to a salesperson’s perceived charisma in a personal selling context by means of high-precision, time-locked coding. This research explores aspects of body language that differentiate salespeople from each other and investigates whether such differences are antecedents of perceived charisma. The findings indicate that certain arm actions, arm postures, and action functions have a significant effect on charismatic appearance and can in turn produce favorable attitudes toward the salesperson.© The Author