Unlocking the insights: data-analytic examinations of social signals in organizational practices

Social media networks;Executive success;Brand personality;Machine learning

Pamuksuz, Utku

关键词: Social media networks;    Executive success;    Brand personality;    Machine learning;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/97612/PAMUKSUZ-DISSERTATION-2017.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Using analytics to understand social data is an emerging research field across different academic disciplines including Information Systems. Information Systems (IS) discipline places the social media-related research at the intersection of people, organizations, and technology. While the recent focus of design science utilizes advanced data mining methods to develop decision-aiding frameworks and extend organizational boundaries by designing novel artifacts; the behavioral focus develops and tests theories that elucidate behaviors at the individual or organizational levels. This thesis comprises three essays aiming to contribute to IS research by both leveraging from the two foundational principles of IS -behavioral science and design science- and applying advanced analytics to further understand the executive, stakeholder, and brand relations. These implementations allow us to elegantly capture several important features of the social signals that have been employed in online networking platforms. In the first two chapters, social signals are examined as internal and external associations of the executives’ career outcomes. The third chapter investigates the social signals from brands’ perspectives. While the first two chapters highlight and examine the relationships of several constructs, the main emphasis of the third chapter lies on designing a valuable information systems tool to complement the theoretical studies and enhance the practical implementations.