ECIS 2020 Research Papers


Companies use social media (e.g., Twitter) to engage with potential applicants and build their reputation as attractive employers. To analyze how Twitter message content influences engagement with these messages, we employ computational linguistics and analyze N=216,828 Tweets collected from the human resource (HR) Twitter accounts of Fortune 500 companies. Our results show that, surprisingly, job-focused content creates less engagement than content focusing on relational aspects at work. We further demonstrate that distinct (vs. generic) content positively affects engagement, whereas emotional content negatively affects engagement. These effects are conditioned on firms’ employer image and not on job posting content. In contrast to prior research, our results suggest that less emotional and more distinct (company-specific) communication is beneficial for increasing engagement. We advance our understanding of the functioning of Twitter as an increasingly popular employer image impression management platform and extend research on employer image management on the Internet.



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