Where can teens find health information? A survey of web portals designed for teen health information seekers

The Web is an important source for health information for most teens with access to the Web (Gray et al, 2005a; Kaiser, 2001). While teens are likely to turn to the Web for health information, research has indicated that their skills in locating, evaluating and using health information are weak (Hansen et al, 2003; Skinner et al, 2003, Gray et al, 2005b). This behaviour suggests that the targeted approach to finding health information that is offered by web portals would be useful to teens. A web portal is the entry point for information on the Web. It is the front end, and often the filter, that users must pass through in order to link to actual content. Unlike general search engines such as Google, content that is linked to a portal has usually been pre-selected and even created by the organization that hosts the portal, assuring some level of quality control. The underlying architecture of the portal is structured and thus offers an organized approach to exploring a specific health topic. This paper reports on an environmental scan of the Web, the purpose of which was to identify and describe portals to general health information, in English and French, designed specifically for teens. It answers two key questions. First of all, what portals exist? And secondly, what are their characteristics? The portals were analyzed through the lens of four attributes: Usability, interactivity, reliability and findability. Usability is a term that incorporates concepts of navigation, layout and design, clarity of concept and purpose, underlying architecture, in-site assistance and, for web content with text, readability. Interactivity relates to the type of interactions and level of engagement required by the user to access health information on a portal. Interaction can come in the form of a game, a quiz, a creative experience, or a communication tool such as an instant messaging board, a forum or blog. Reliability reflects the traditional values of accuracy, currency, credibility and bias, and in the web-based world, durabililty. Findability is simply the ease with which a portal can be discovered by a searcher using the search engine that is most commonly associated with the Web by young people - Google - and using terms related to teen health. Findability is an important consideration since the majority of teens begin their search for health information using search engines (CIBER, 2008; Hansen et al, 2003). The content linked to by the portals was not evaluated, nor was the portals’ efficacy as a health intervention. Teens looking for health information on the Web in English have a wide range of choices available but French-language portals are much rarer and harder to find. A majority of the portals found and reviewed originated from hospitals, associations specializing in a particular disease, and governmental agencies, suggesting that portals for teens on health related topics are generally reliable. However, only a handful of the portals reviewed were easy to find, suggesting that valuable resources for teens remain buried in the Web

Finding co-solvers on Twitter, with a little help from Linked Data

In this paper we propose a method for suggesting potential collaborators for solving innovation challenges online, based on their competence, similarity of interests and social proximity with the user. We rely on Linked Data to derive a measure of semantic relatedness that we use to enrich both user profiles and innovation problems with additional relevant topics, thereby improving the performance of co-solver recommendation. We evaluate this approach against state of the art methods for query enrichment based on the distribution of topics in user profiles, and demonstrate its usefulness in recommending collaborators that are both complementary in competence and compatible with the user. Our experiments are grounded using data from the social networking service Twitter.com

A Broad Evaluation of the Tor English Content Ecosystem

Tor is among most well-known dark net in the world. It has noble uses, including as a platform for free speech and information dissemination under the guise of true anonymity, but may be culturally better known as a conduit for criminal activity and as a platform to market illicit goods and data. Past studies on the content of Tor support this notion, but were carried out by targeting popular domains likely to contain illicit content. A survey of past studies may thus not yield a complete evaluation of the content and use of Tor. This work addresses this gap by presenting a broad evaluation of the content of the English Tor ecosystem. We perform a comprehensive crawl of the Tor dark web and, through topic and network analysis, characterize the types of information and services hosted across a broad swath of Tor domains and their hyperlink relational structure. We recover nine domain types defined by the information or service they host and, among other findings, unveil how some types of domains intentionally silo themselves from the rest of Tor. We also present measurements that (regrettably) suggest how marketplaces of illegal drugs and services do emerge as the dominant type of Tor domain. Our study is the product of crawling over 1 million pages from 20,000 Tor seed addresses, yielding a collection of over 150,000 Tor pages. We make a dataset of the intend to make the domain structure publicly available as a dataset at https://github.com/wsu-wacs/TorEnglishContent.Comment: 11 page

Is Stack Overflow Overflowing With Questions and Tags

Programming question and answer (Q & A) websites, such as Quora, Stack Overflow, and Yahoo! Answer etc. helps us to understand the programming concepts easily and quickly in a way that has been tested and applied by many software developers. Stack Overflow is one of the most frequently used programming Q\&A website where the questions and answers posted are presently analyzed manually, which requires a huge amount of time and resource. To save the effort, we present a topic modeling based technique to analyze the words of the original texts to discover the themes that run through them. We also propose a method to automate the process of reviewing the quality of questions on Stack Overflow dataset in order to avoid ballooning the stack overflow with insignificant questions. The proposed method also recommends the appropriate tags for the new post, which averts the creation of unnecessary tags on Stack Overflow.Comment: 11 pages, 7 figures, 3 tables Presented at Third International Symposium on Women in Computing and Informatics (WCI-2015

Quantifying Biases in Online Information Exposure

Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on online technologies such as search engines and social media may limit exposure to diverse points of view and make us vulnerable to manipulation by disinformation. In this paper, we mine a massive dataset of Web traffic to quantify two kinds of bias: (i) homogeneity bias, which is the tendency to consume content from a narrow set of information sources, and (ii) popularity bias, which is the selective exposure to content from top sites. Our analysis reveals different bias levels across several widely used Web platforms. Search exposes users to a diverse set of sources, while social media traffic tends to exhibit high popularity and homogeneity bias. When we focus our analysis on traffic to news sites, we find higher levels of popularity bias, with smaller differences across applications. Overall, our results quantify the extent to which our choices of online systems confine us inside "social bubbles."Comment: 25 pages, 10 figures, to appear in the Journal of the Association for Information Science and Technology (JASIST

Understanding Mobile Search Task Relevance and User Behaviour in Context

Improvements in mobile technologies have led to a dramatic change in how and when people access and use information, and is having a profound impact on how users address their daily information needs. Smart phones are rapidly becoming our main method of accessing information and are frequently used to perform `on-the-go' search tasks. As research into information retrieval continues to evolve, evaluating search behaviour in context is relatively new. Previous research has studied the effects of context through either self-reported diary studies or quantitative log analysis; however, neither approach is able to accurately capture context of use at the time of searching. In this study, we aim to gain a better understanding of task relevance and search behaviour via a task-based user study (n=31) employing a bespoke Android app. The app allowed us to accurately capture the user's context when completing tasks at different times of the day over the period of a week. Through analysis of the collected data, we gain a better understanding of how using smart phones on the go impacts search behaviour, search performance and task relevance and whether or not the actual context is an important factor.Comment: To appear in CHIIR 2019 in Glasgow, U