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Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
The Impact of Content Commenting on User Continuance in O...
Langtao Chen · 2020-01-24 · via cs.HC updates on arXiv.org

Online question-and-answer (Q&A) communities provide convenient and innovative ways for participants to share information and collaboratively solve problems with others. A growing challenge for those Q&A communities is to encourage and maintain ongoing user participation. From the perspective of motivational affordances, this study proposes a research framework to explain the effect of content commenting on user continuance behavior in online Q&A communities. The moderating role of participant's tenure in the relationship between content commenting and user continuance is also explored. Using a longitudinal panel dataset collected from a large online Q&A community, this research empirically tests the effect of content commenting on continued user participation in the Q&A community. The results show that both comment receipt and comment provisioning are important motivating factors for user continuance in the community. Specifically, received comments on questions submitted by a participant have a positive effect on the participant's continuance of posting questions, while answer comments both received and posted by a participant have positive impact on user continuance of posting answers in the community. In addition, tenure in the community is indeed found to have a significant negative moderating effect on the relationship between content commenting and user continuance. This research not only offers a more nuanced theoretical understanding of how content commenting affects continued user involvement and how participants' tenure in the community moderates the impact of content commenting, but also provides implications for improving user continuance in online Q&A communities.