41,486 research outputs found
People on Drugs: Credibility of User Statements in Health Communities
Online health communities are a valuable source of information for patients
and physicians. However, such user-generated resources are often plagued by
inaccuracies and misinformation. In this work we propose a method for
automatically establishing the credibility of user-generated medical statements
and the trustworthiness of their authors by exploiting linguistic cues and
distant supervision from expert sources. To this end we introduce a
probabilistic graphical model that jointly learns user trustworthiness,
statement credibility, and language objectivity. We apply this methodology to
the task of extracting rare or unknown side-effects of medical drugs --- this
being one of the problems where large scale non-expert data has the potential
to complement expert medical knowledge. We show that our method can reliably
extract side-effects and filter out false statements, while identifying
trustworthy users that are likely to contribute valuable medical information
Challenges to Teaching Credibility Assessment in Contemporary Schooling
Part of the Volume on Digital Media, Youth, and CredibilityThis chapter explores several challenges that exist to teaching credibility assessment in the school environment. Challenges range from institutional barriers such as government regulation and school policies and procedures to dynamic challenges related to young people's cognitive development and the consequent difficulties of navigating a complex web environment. The chapter includes a critique of current practices for teaching kids credibility assessment and highlights some best practices for credibility education
"Looking behind the veil": invisible corporate intangibles, stories, structure and the contextual information content of disclosure
Purpose – This paper aims to use a grounded theory approach to reveal that corporate private disclosure content has structure and this is critical in making "invisible" intangibles in corporate value creation visible to capital market participants.
Design/methodology/approach – A grounded theory approach is used to develop novel empirical patterns concerning the nature of corporate disclosure content in the form of narrative. This is further developed using literature of value creation and of narrative.
Findings – Structure to content is based on common underlying value creation and narrative structures, and the use of similar categories of corporate intangibles in corporate disclosure cases. It is also based on common change or response qualities of the value creation story as well as persistence in telling the core value creation story. The disclosure is a source of information per se and also creates an informed context for capital market participants to interpret the meaning of new events in a more informed way.
Research limitations/implications – These insights into the structure of private disclosure content are different to the views of relevant information content implied in public disclosure means such as in financial reports or in the demands of stock exchanges for "material" or price sensitive information. They are also different to conventional academic concepts of (capital market) value relevance.
Practical implications – This analysis further develops the grounded theory insights into disclosure content and could help improve new disclosure guidance by regulators.
Originality/value – The insights create many new opportunities for developing theory and enhancing public disclosure content. The paper illustrates this potential by exploring new ways of measuring the value relevance of this novel form of contextual information and associated benchmarks. This connects value creation narrative to a conventional value relevance view and could stimulate new types of market event studies
The Best Answers? Think Twice: Online Detection of Commercial Campaigns in the CQA Forums
In an emerging trend, more and more Internet users search for information
from Community Question and Answer (CQA) websites, as interactive communication
in such websites provides users with a rare feeling of trust. More often than
not, end users look for instant help when they browse the CQA websites for the
best answers. Hence, it is imperative that they should be warned of any
potential commercial campaigns hidden behind the answers. However, existing
research focuses more on the quality of answers and does not meet the above
need. In this paper, we develop a system that automatically analyzes the hidden
patterns of commercial spam and raises alarms instantaneously to end users
whenever a potential commercial campaign is detected. Our detection method
integrates semantic analysis and posters' track records and utilizes the
special features of CQA websites largely different from those in other types of
forums such as microblogs or news reports. Our system is adaptive and
accommodates new evidence uncovered by the detection algorithms over time.
Validated with real-world trace data from a popular Chinese CQA website over a
period of three months, our system shows great potential towards adaptive
online detection of CQA spams.Comment: 9 pages, 10 figure
- …