Community Question Answering: From Recent Advances in Methods, Techniques, Models and Applications to Future Perspectives

Dear Colleagues,

Community question answering (CQA) encompasses a broad class of services for knowledge sharing and collaborative learning that allow askers to post questions upon specific information needs, in an attempt to receive satisfactory responses from expert answerers of the consulted community. Essentially, in CQA, the information needs of askers together with the wisdom, reply willingness, and collective intelligence of answerers form altogether a human and social computation system. Within the latter, askers and answerers operate as human sensors. The former report the emergence of an information need in the community. The latter act individually and/or cooperatively, to sense and process the information needs posted by askers in their questions, so that these latter can be replied to in a timely and satisfactory manner through high-quality responses. Hitherto, the increasing relevance and popularity of CQA have fostered a wide spectrum of contributions from both academia and industry. Moreover, because of the growing number of such contributions straddling multiple research fields, CQA has rapidly developed into a multidisciplinary area that lies at the crossroads of natural language processing, recommender systems, social computing, knowledge representation, information retrieval, data mining, machine learning, and data science.

The aim of this Special Issue is to explore the latest advances in all tasks of CQA by collecting innovative developments, in which fundamental and practical aspects of interest are addressed. To this end, we solicit original contributions including theoretical as well as application-oriented studies. In particular, we encourage new interdisciplinary approaches which implement synergies among perspectives, developments, and progress across different fields. Additionally, we solicit novel studies in which multiple aspects of interests in CQA are considered jointly. We also welcome systematic reviews of the existing literature, with a special focus on the latest frontier of research as well as the open issues, unaddressed aspects, new trends, emerging applications, and future developments.

Finally, you are more than welcome to attend the “Second International Workshop on Expert Recommendation for Community Question Answering”(XPERT4CQA) (https://sites.google.com/icar.cnr.it/xpert4cqa-sdm2022/home), where the extensions of previously published works are invited, as long as these include at least 50% new material devoted to unprecedented and significant contributions, which must be clearly identified in the introduction.

The topics of interest for all submissions to this Special Issue include, but are not limited to:

• Foundations, testing and best practices of innovative CQA methods, techniques, models, tools and systems. Design of new CQA systems and applications.
• Knowledge creation, management and sharing in community-based questioning and answering.
• Wisdom of the crowd. Collective intelligence. 
• Case studies and analytics of CQA communities.
• Evolutionary dynamics of questioning, answering, users and communities.
• CQA and mobile environments.
• Spatial, temporal and social context of mobile CQA users.
• User context analysis and CQA.
• Context-aware questioning and answering in mobile CQA environments.
• Social sensing and CQA.
• Mobile crowdsensing and CQA.
• CQA user modeling and profiling: behavioral patterns, susceptibility, authority, expertise, reputation, influence, activity, willingness to reply and trustworthiness.
• CQA content and topic modeling.
• Knowledge representation and CQA.
• Information diffusion and CQA.
• Spread of misinformation/disinformation and CQA.
• Promotion of active user participation.
• Post quality and long-term value.
• Exposure to posts.
• User roles and CQA.
• Post retrieval, suggestion and summarization.
• CQA and web searches.
• Question routing, expert finding, answerer recommendation.
• Question routing for collaborative answering.
• Tag recommendation.

Dr. Gianni Costa
Dr. Riccardo Ortale
Guest Editors

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