Obtaining knowledge from online Q and A sites introduces significant epistemic reliability problems.
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Studies on community question-answering platforms demonstrate that solution quality varies significantly with audience size and that low-quality answers can lead to user mistrust, highlighting inherent epistemic reliability issues.
Question Answering websites have evolved into one of the most important platforms for knowledge sharing and problem solving online. Despite widespread adoption of Q&As by technical communities as well as an abundance of domain experts, many questions fail to attract a sufficient audience to obtain a good solution or any solution at all. We investigate the effects of crowd size on solution quality in Stack Exchange Q&A communities on topics related to big data. We find that three distinct levels of group size in the crowd (topic audience size, question audience size, and number of contributors) affect solution quality. Therefore, we argue that group size in the crowd is not unitary, but rather a multi-level construct. This work advances a theoretical model of group size in the crowd and the relation between crowd size and performance. The work also has practical implications for system designers trying to route crowds to problems efficiently.
The growth of digital platforms has led to the proliferation of Online Communities, providing individuals with opportunities to seek help and share knowledge. A key challenge of help-related platforms that address technical questions (i.e., utilitarian, rather than opinion or supportive) is to ensure the contributions address seekers’ specific information needs. Despite growing academic interest in such platforms, research has mainly focused on factors that influence the quantity of contributions, ignoring whether these contributions effectively helped the seekers. To fill this research gap, this study draws upon theories of self-determination and motivation crowding to examine contributing behaviors that result in successful helping. By analyzing a rich dataset collected from an online Q&A platform, we find that gains in a help provider’s past rewards positively influence the success of contribution. Further, while previous studies suggest that external rewards result in a high quantity of contribution, our findings show that an inflated frequency of contribution leads to a crowding-out effect. Specifically, the contribution frequency has a curvilinear relationship with the success of the contribution. Taken together, these findings demonstrate there is a need to revisit the gamification mechanism on help-related platforms to ensure the success of knowledge contribution. This is crucial for the sustainability of these platforms as low-quality answers can lead users to mistrust and eventually leave the platform.
information. Similar sites allow individuals to copy and paste misinformation into a search engine and the site will investigate it. Some sites exist to address
Misinformation is incorrect or misleading information. Whereas misinformation can exist with or without specific malicious intent, disinformation is deliberately deceptive and intentionally propagated. Misinformation is typically spread unintentionally, mostly caused by a lack of knowledge, an error, or simply a misunderstanding, which contrasts with disinformation. Misinformation can include inac
Automated detection systems (e.g. to flag or add context and resources to content)
Provenance enhancing technology (i.e. better enabling people to determine the veracity of a claim, image, or video)
APIs for research (i.e. for usage to detect, understand, and counter misinformation)
Active bystanders (e.g. corrective commenting)
Community moderation (usually of unpaid and untrained, often independent, volunteers)
Anti-virals (e.g. limiting the number of times a message can be forwarded in privacy-respecting encrypted chats)
Collective intelligence (examples being Wikipedia where multiple editors refine encyclopedic articles, and question-and-answer sites where outputs are also evaluated by others similar to peer-review)
Media literacy (increasing citizens' ability to use ICTs to find, evaluate, create, and communicate information, an essential skill for citizens of all ages)
Media literacy is taught in Estonian public schools – from kindergarten through to high school – since 2010 and "accepted 'as important as [...] writing or reading'"
New Jersey mandated K-12 students to learn information literacy
"Inoculation" via educational videos shown to adults is being explored
Broadly described, the report recommends building resilience to scientific misinformation and a healthy online information environment and not having offending content removed. It cautions that censorship could e.g. drive misinformation and associated communities "to harder-to-address corners of the internet".
Online misinformation about climate change can be counteracted through different measures at different stages. Prior to misinformation exposure, education and "inoculation" are proposed. Technological solutions, such as early detection of bots and ranking and selection algorithms are suggested as ongoing mechanisms. Post misinformation, corrective and collaborator messaging can be used to counter climate change misinformation. Incorporating fines and similar consequences has also been suggested.
The International Panel on the Information Environment was launched in 2023 as a consortium of over 250 scientists working to develop effective countermeasures to misinformation and other problems…
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