Related papers: Supporting Answerers with Feedback in Social Q&A
As social Q&A sites gain popularity, it is important to understand how users judge the authoritativeness of users and content, build reputation, and identify and promote high quality content. We conducted a study of emerging social Q&A site…
Online consumer reviews play a crucial role in guiding purchase decisions by offering insights into product quality, usability, and performance. However, the increasing volume of user-generated reviews has led to information overload,…
AI-based writing assistants are ubiquitous, yet little is known about how users' mental models shape their use. We examine two types of mental models -- functional or related to what the system does, and structural or related to how the…
Online coding environments can help support computing students gain programming practice at their own pace. Especially informative feedback can be beneficial during such self-guided, independent study phases. This research aims at the…
Software qualities such as usability or reliability are among the strongest determinants of mobile app user satisfaction and constitute a significant portion of online user feedback on software products, making it a valuable source of…
Many online platforms incorporate engagement signals, such as likes, into their interface design to boost engagement. However, these signals can unintentionally elevate content that may not support normatively desirable behavior, especially…
Questions form an integral part of our everyday communication, both offline and online. Getting responses to our questions from others is fundamental to satisfying our information need and in extending our knowledge boundaries. A question…
Crowd-sourcing deals with solving problems by assigning them to a large number of non-experts called crowd using their spare time. In these systems, the final answer to the question is determined by summing up the votes obtained from the…
Community-based question answering (CQA) platforms are crowd-sourced services for sharing user expertise on various topics, from mechanical repairs to parenting. While they naturally build-in an online social network infrastructure, they…
In ad-hoc retrieval, evaluation relies heavily on user actions, including implicit feedback. In a conversational setting such signals are usually unavailable due to the nature of the interactions, and, instead, the evaluation often relies…
Community Question-Answering platforms, such as Stack Overflow (SO), are valuable knowledge exchange and problem-solving resources. These platforms incorporate mechanisms to assess the quality of answers and participants' expertise, ideally…
Large language models are increasingly discussed and used as tools that may assist with scholarly peer review, but empirical evidence regarding how authors use and perceive AI-based feedback remains limited. This paper reports findings from…
AI is reshaping academic research, yet its role in peer review remains polarising and contentious. Advocates see its potential to reduce reviewer burden and improve quality, while critics warn of risks to fairness, accountability, and…
If large language models like GPT-3 preferably produce a particular point of view, they may influence people's opinions on an unknown scale. This study investigates whether a language-model-powered writing assistant that generates some…
Product-specific community question answering platforms can greatly help address the concerns of potential customers. However, the user-provided answers on such platforms often vary a lot in their qualities. Helpfulness votes from the…
Conversational interfaces are currently on the rise: more and more applications rely on a chat-like interaction pattern to increase their acceptability and to improve user experience. Also in the area of questionnaire design and…
The correct specification of reward models is a well-known challenge in reinforcement learning. Hand-crafted reward functions often lead to inefficient or suboptimal policies and may not be aligned with user values. Reinforcement learning…
The principle of rewarding a crowd for surprisingly common answers has been used in the literature for designing a number of truthful information elicitation mechanisms. A related method has also been proposed in the literature for better…
Social media usage has been shown to have both positive and negative consequences for users' mental health. Several studies indicated that peer feedback plays an important role in the relationship between social media use and mental health.…
Social media systems rely on user feedback and rating mechanisms for personalization, ranking, and content filtering. However, when users evaluate content contributed by fellow users (e.g., by liking a post or voting on a comment), these…