4,530 research outputs found
Maximizing Friend-Making Likelihood for Social Activity Organization
The social presence theory in social psychology suggests that
computer-mediated online interactions are inferior to face-to-face, in-person
interactions. In this paper, we consider the scenarios of organizing in person
friend-making social activities via online social networks (OSNs) and formulate
a new research problem, namely, Hop-bounded Maximum Group Friending (HMGF), by
modeling both existing friendships and the likelihood of new friend making. To
find a set of attendees for socialization activities, HMGF is unique and
challenging due to the interplay of the group size, the constraint on existing
friendships and the objective function on the likelihood of friend making. We
prove that HMGF is NP-Hard, and no approximation algorithm exists unless P =
NP. We then propose an error-bounded approximation algorithm to efficiently
obtain the solutions very close to the optimal solutions. We conduct a user
study to validate our problem formulation and per- form extensive experiments
on real datasets to demonstrate the efficiency and effectiveness of our
proposed algorithm
How Employee Use of Generative Artificial Intelligence Affects Self-Evaluation: Investigating Implications for Job Insecurity and Career Commitment
This research delves into the transformative influence of Generative Artificial Intelligence (GenAI) on the self-evaluation processes of employees within contemporary organizations. In an era marked by rapid technological advancements, the integration of AI into various facets of the workplace is reshaping traditional paradigms. We use Self-Evaluation Maintenance (SEM) Model, which is our theoretical lens, and combining with the concept of Core Self-Evaluation (CSE) to conduct our research model. This study seeks to elucidate whether the usage of GenAI, specifically in the context of performance compares to GenAI, and then the impact on CSE, which we plan to use in this research, has discernible effects on how employees perceive and evaluate their own contributions. In addition, we adapt various reliable scales to assess the constructs in our research model. This research employs surveys and content analysis of questionnaire data to investigate the perceptions of employees in organizations that have introduced GenAI-driven tools for performance appraisal. The objective is to determine whether these tools, by providing real-time feedback, personalized recommendations, and novel evaluation metrics, result in changed self-perceptions and attitudes towards one\u27s work
- …