Two sides of the coin: measuring and communicating the trustworthiness of online information

Abstract

Information is the currency of the digital age -it is constantly communicated, exchanged and bartered, most commonly to support human understanding and decision-making. While the Internet and Web 2.0 have been pivotal in streamlining many of the information creation and dissemination processes, they have significantly complicated matters for users as well. Most notably, the substantial increase in the amount of content available online has introduced an information overload problem, while also exposing content with largely unknown levels of quality, leaving many users with the difficult question of, what information to trust? In this article we approach this problem from two perspectives, both aimed at supporting human decision-making using online information. First, we focus on the task of measuring the extent to which individuals should trust a piece of openly-sourced information (e.g., from Twitter, Facebook or a blog); this considers a range of factors and metrics in information provenance, quality and infrastructure integrity, and the person's own preferences and opinion. Having calculated a measure of trustworthiness for an information item, we then consider how this rating and the related content could be communicated to users in a cognitively-enhanced manner, so as to build confidence in the information only where and when appropriate. This work concentrates on a range of potential visualisation techniques for trust, with special focus on radar graphs, and draws inspiration from the fields of Human-Computer Interaction (HCI), System Usability and Risk Communication. The novelty of our contribution stems from the comprehensive approach taken to address this very topical problem, ensuring that the trustworthiness of openly-sourced information is adequately measured and effectively communicated to users, thus enabling them to make informed decisions.

Tag clouds with a twist: using tag clouds coloured by information’s trustworthiness to support situational awareness

“…In this article, we propose combining this technique with our previous research on the topic of analysing and presenting the trustworthiness of online information [7,8]. The presumed workflow would be as follows:…”

“…Considering this ability, a prime application of tag clouds has been the creation and display of summaries of large amounts of text [4]. Our approach aims to combine the summary capability of this technique with our previous work on assessing the trustworthiness of information [7,8], so as to create specialised clouds with words (or parts thereof) coloured according to the trustworthiness of the underlying content (i.e., the different information items used to generate the cloud). Our core goal is to develop and then evaluate the use of such an approach in summarising large amounts of information and then providing individuals with a quick, helpful and accurate overview of the situation.…”

Escalation of TRUST analysis in web

“…These factors are: Topic, Context and criticality, Popularity, Authority, Direct Experience, Recommendation, Related Resources, Provenance, User Expertise, Bias, Incentive, Limited Resources, Agreement, Specificity, Likelihood, Age, Appearance, Deception and Recency [8]. In [9], focus is done on effective representation of well-informed decisions in addition of effectively calculating it. They pose that credibility and quality are the two pillars to measure trustworthiness of any information and is perceived differently by different users.…”

“…Three bins were used for categorizing as it was found in a direct study in [9] that five or more levels of trust instead of three becomes "more challenging for individuals to perceive". The same is supported by [17].…”

“…Since the main aim is to evaluate trust in information led or content driven websites, we have collected data of hundred medical websites over the period of one month of These websites were chosen in such a manner that we can classify them into three trust categories as direct studies in [9] and [17] strongly suggests that trust should not have more than three categories.…”