Emotion in enterprise social media systems

Abstract

Purpose The purpose of this paper is to investigate enterprise social media systems and quantified gender and status influences on emotional content presented in these systems. Design/methodology/approach Internal social media messages were collected from a global software company running an enterprise social media system. An indirect observatory test using Berlo’s “source–message–channel–receiver” model served as a framework to evaluate sender, message, channel and receiver for each text. These texts were categorized by gender and status using text analytics with SAP SA to produce sentiment indications. Findings Results reveal women use positive language 2.1 times more than men. Senior managers express positive language 1.7 times more than non-managers, and feeling rules affect all genders and statuses, but not necessarily as predicted by theory. Other findings show that public messages contained less emotional content, and women expressed more positivity to lower status colleagues. Men expressed more positivity to those in higher positions. Many gender and status stereotypes found in face-to-face studies are also present in digital enterprise social networks. Research limitations/implications Limitations include generalizability: all data were collected from a single enterprise social media system. Practical implications Managers establishing codes of conduct for social media use will find this research useful, particularly when promoting awareness of emotional expressiveness in online venues with subordinate colleagues. Originality/value This study offers a behavioral measurement approach free from validity issues found in self-reported surveys, direct observations and interviews. The collected data offered new perspectives on existing social theories within a new environment of computerized, enterprise social media.

Guest editorial: Emotions in the digitalised workplace

“…As for qualitative methods for data collection, it can be seen that ethnography and observation have been deployed just as often as interviews, and that 10%, in total, made use of digital data, e.g. Reychav et al (2019), who used SAP's HANA Text Analysis to measure the sentiment in each message for a total of 29K messages from one organisation's Enterprise Social Network (ESN), Yammer.…”

Linking organizational members' social-related use of enterprise social media (ESM) to their fashion behaviors: the social learning and stimulus-organism-response theories

“…Compared to the public platforms, ESM technology is more convenient to be monitored and controlled by the managers (Olfat et al, 2019). Thus, despite the fact that ESM technologies in terms of physical design and motivations are similar to the conventional platforms (Fulk and Yuan, 2013;Tabarsa et al, 2018Tabarsa et al, , 2019Reychav et al, 2019), their outcomes in the workplace can be soundly different (Chen and Wei, 2019).…”

“…Ali-Hassan et al (2015) have considered three social-related, work-related (cognitive), and hedonic motivations for the use of social media in the workplace. Based on Reychav et al (2019), ESM and public platforms are the same in terms of motivations. Thus, the motives introduced by Ali- Hassan et al (2015) are also generalizable to the employees' use of ESM, as previous studies have done so (e.g.…”

“…The provided information by social-related use of ESM can also be presented in the shape of some textual and review posts (Fulk and Yuan, 2013;Tabarsa et al, 2018Tabarsa et al, , 2019Reychav et al, 2019). For example, employees can review the fashion products they have already used and their purchase experiences (expertise) to give some advice to other users on ESM.…”

Service quality in multichannel fashion retailing: an exploratory study

“…Constructivist ethnography wishes to understand what is taking place in specific contexts and emphasises experiential validity and, through thick interpretation, determines clear indications of how people react to phenomenon through emphasising 'the rich, real-world context in which the phenomenon occurs' (Eisenhardt, 2007, p. 25). Indeed, data collection is based on the requirements of experiential rather than measurable validity which requires in-depth observation (through interviews and focus groups) of multichannel customers in an attempt to construct or develop theory, using a single case study strategy (Reychav, Inbar, Simon, McHaney, & Zhu, 2019). Surveys normally provide quantitative data and enable measurement validity or reliability and non-disputed generalisation or external reality.…”