Quality of health answers in social Q&amp;A

Oh, Sanghee; Yi, Yong Jeong; Worrall, Adam

doi:10.1002/meet.14504901075

Cited by 25 publications

(25 citation statements)

References 13 publications

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“…The paper by Oh et al 127 investigates the issue of quality of online health answers in social question answering (QA) systems, considering also source credibility. This paper presents a preliminary user study involving 40 participants who have rated 400 health answers each with a 5-point Likert scale according to 10 evaluation criteria.…”

Section: Health Information Credibility In Social Mediamentioning

confidence: 99%

Credibility in social media: opinions, news, and health information—a survey

Viviani

Pasi

2017

WIREs Data Min & Knowl

151

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In the Social Web scenario, where large amounts of User Generated Content diffuse through Social Media, the risk of running into misinformation is not negligible. For this reason, assessing and mining the credibility of both sources of information and information itself constitute nowadays a fundamental issue. Credibility, also referred as believability, is a quality perceived by individuals, who are not always able to discern with their cognitive capacities genuine information from the fake one. For this reason, in the recent years several approaches have been proposed to automatically assess credibility in Social Media. Most of them are based on data‐driven models, i.e., they employ machine‐learning techniques to identify misinformation, but recently also model‐driven approaches are emerging, as well as graph‐based approaches focusing on credibility propagation. Since multiple social applications have been developed for different aims and in different contexts, several solutions have been considered to address the issue of credibility assessment in Social Media. Three of the main tasks facing this issue and considered in this article concern: (1) the detection of opinion spam in review sites, (2) the detection of fake news and spam in microblogging, and (3) the credibility assessment of online health information. Despite the high number of interesting solutions proposed in the literature to tackle the above three tasks, some issues remain unsolved; they mainly concern both the absence of predefined benchmarks and gold standard datasets, and the difficulty of collecting and mining large amount of data, which has not yet received the attention it deserves. WIREs Data Mining Knowl Discov 2017, 7:e1209. doi: 10.1002/widm.1209 This article is categorized under: Algorithmic Development > Web Mining Application Areas > Science and Technology Technologies > Machine Learning

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Section: Health Information Credibility In Social Mediamentioning

confidence: 99%

Credibility in social media: opinions, news, and health information—a survey

Viviani

Pasi

2017

WIREs Data Min & Knowl

151

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“…By contrast, information researchers have examined a number of health forums to understand what kind of information is exchanged and how the information is helpful (Ma, Chen, & Xiao, ; Oh, ; Preece & Maloney‐Krichmar, ). Different forums may emphasize information or social support, but information science has tended to focus on the informational aspects, mining content to report on the types of information exchanged, drawing typologies of the information exchanged or examining characteristics, context, or quality of information (Burnett, ; Oh, Yi, & Worrall, ; Stvilia, Mon, & Yi, ; Zhang, ) to the exclusion of social support.…”

Section: Introductionmentioning

confidence: 99%

“They are always there for me”: The convergence of social support and information in an online breast cancer community

Rubenstein

2014

Asso for Info Science & Tech

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This research examines interactions among members of an online breast cancer community, focusing on how information and social support were exchanged, how these exchanges influenced health decisions, and how the community was integrated into participants' everyday lives. This article is the result of a 2‐year ethnography comprising online archives analysis, participant observation, and 31 interviews. In the course of the research, the findings revealed that, not only did participants exchange valuable information and helpful social support, there was often little separation between the two, with each overlaying the other throughout most interactions. Expressions of support permeated many informational messages and at the same time served as information to participants. This article argues that social support and information were inextricably connected within participant interactions and that social support is, itself, a form of information that impacts actions and emotional experiences, contributing to participants being able to make sense of their experiences and to move forward both physically and emotionally. This research builds on work in information science that looks at the ways in which people exchange information in informal environments and extends that research by drawing on conceptualizations of social support to exhibit the connections between social support and information.

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“…In the late 1990s, the diffusion of the Internet into the public sphere rapidly made it a popular space for general consumers to seek health information (Eysenbach, 2000;Morahan-Martin, 2004). More recently, the development of Web 2.0 technologies led to the emergence of an array of new forms of sources, including online communities, wikis, social Q&A, and social networking sites (SNSs), where consumers not only look for information, but also share personal stories, participate in discussions, and collaboratively construct knowledge (Eysenbach, Powell, Englesakis, Rizo, & Stern, 2004;Laurent & Vickers, 2009;Oh, Yi, & Worrall, 2012). This recent development has made the current health information environment unprecedentedly diverse and complex.…”

Section: Introductionmentioning

confidence: 99%

Beyond quality and accessibility: Source selection in consumer health information searching

Zhang

2014

Asso for Info Science & Tech

100

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A systematic understanding of factors and criteria that affect consumers' selection of sources for health information is necessary for the design of effective health information services and information systems. However, current studies have overly focused on source attributes as indicators for 2 criteria, source quality and accessibility, and overlooked the role of other factors and criteria that help determine source selection. To fill this gap, guided by decision-making theories and the cognitive perspective to information search, we interviewed 30 participants about their reasons for using a wide range of sources for health information. Additionally, we asked each of them to report a critical incident in which sources were selected to fulfill a specific information need. Based on the analysis of the transcripts, 5 categories of factors were identified as influential to source selection: source-related factors, user-related factors, user-source relationships, characteristics of the problematic situation, and social influences. In addition, about a dozen criteria that mediate the influence of the factors on source-selection decisions were identified, including accessibility, quality, usability, interactivity, relevance, usefulness, familiarity, affection, anonymity, and appropriateness. These results significantly expanded the current understanding of the nature of costs and benefits involved in source-selection decisions, and strongly indicated that a personalized approach is needed for information services and information systems to provide effective access to health information sources for consumers. IntroductionInformation sources are containers or carriers of information (Kuhlthau, 1999;Morrison & Vancouver, 2000;O'Reilly, 1982). Selecting a source is often the first step in information seeking (Belkin, Oddy, & Brooks, 1982;Marchionini, 1997;Savolainen, 2006;Wilson, 1981). Thus, source selection naturally has a direct impact on the success of information search attempts. This impact may be more significant in the health domain, as the quality and completeness of information varies greatly across different sources (Purcell, Wilson, & Delamothe, 2002;Yeung & Mortensen, 2012). Such variances could cause users to develop different mental models of diseases and form different health beliefs, which will subsequently lead to different health behaviors and decisions (Kealey & Berkman, 2010).Health information is available from many different sources. More traditional ones include interpersonal sources (doctors, family, and friends), mass media (TV, newspapers, magazines, and radio), published literature, books, pamphlets, and telephone advice lines (e.g., cancer information services) (Cangelosi & Markham, 1994;Gollop, 1997;Lenz, 1984;Manfredi, Czaja, Buis, & Derk, 1993;O'Malley, Kerner, & Johnson, 1999;Pennbridge, Moya, & Rodrigues, 1999). In the late 1990s, the diffusion of the Internet into the public sphere rapidly made it a popular space for general consumers to seek health information (Eysenbach, 2000;Morahan...

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Quality of health answers in social Q&A

Cited by 25 publications

References 13 publications

Credibility in social media: opinions, news, and health information—a survey

Credibility in social media: opinions, news, and health information—a survey

“They are always there for me”: The convergence of social support and information in an online breast cancer community

Beyond quality and accessibility: Source selection in consumer health information searching

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