Improving Categorisation in Social Media Using Hyperlinks to Structured Data Sources

Abstract. Social media presents unique challenges for topic classifica-tion, including the brevity of posts, the informal nature of conversations, and the frequent reliance on external hyperlinks to give context to a con-versation. In this paper we investigate the usefulness of these external hyperlinks for categorising the topic of individual posts. We focus our analysis on objects that have related metadata available on the Web, either via APIs or as Linked Data. Our experiments show that the in-clusion of metadata from hyperlinked objects in addition to the original post content significantly improved classifier performance on two dis-parate datasets. We found that including selected metadata from APIs and Linked Data gave better results than including text from HTML pages. We investigate how this improvement varies across different top-ics. We also make use of the structure of the data to compare the use-fulness of different types of external metadata for topic classification in a social media dataset

Spotting the diffusion of New Psychoactive Substances over the Internet

Online availability and diffusion of New Psychoactive Substances (NPS) represent an emerging threat to healthcare systems. In this work, we analyse drugs forums, online shops, and Twitter. By mining the data from these sources, it is possible to understand the dynamics of drugs diffusion and their endorsement, as well as timely detecting new substances. We propose a set of visual analytics tools to support analysts in tackling NPS spreading and provide a better insight about drugs market and analysis

From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Systematic review of the types of methods and approaches used to assess the effectiveness of healthcare information websites

Author version made available in accordance with the publisher's policyThe objective of this systematic review was to identify types of approaches and methods used to evaluate the effectiveness of healthcare information websites. Simple usage data may not be sufficient to assess if the desired healthcare outcomes were achieved or to determine the relative effectiveness of different web resources on the same health topic. To establish the state of the knowledge base on assessment methods used to determine the effectiveness of healthcare websites, a structured search of the literature was conducted in Ovid Medline resulting in 1,611 articles retrieved, of which 240 met the inclusion criteria for this review. Results of this review found that diverse evaluation methods were used to measure the effectiveness of healthcare websites. These evaluation methods were used during development, prior to release, and after release. Economic assessment was rare and most evaluations looked at content issues such as readability scores. A number of studies did try to assess the usefulness of websites but few studies looked at behaviour change or knowledge transfer following engagement with the designated health website. To assess the effectiveness of the knowledge transfer of healthcare information through the online environment, multiple methods may need to be used to evaluate healthcare websites and may need to be undertaken at all stages of the website development process

Towards an understanding of corporate web identity

No abstract available

Emerging Communication Technologies and Public Health Information Dissemination

Health promotion is a critical constituent of the public health system. Its primary objective is the empowerment of individuals and communities in the interest of positively influencing health behaviours and outcomes. One of the main ways in which successful health promotion is achieved is by the dissemination of relevant health information to individuals and communities. As global health costs rise to match the demands of an increasing and ageing population, such delivery of cost-effective public health information is explored. The recent advances in communication technologies have led to the development of social digital platforms (Web 2.0), with unprecedented opportunities for the extensive dissemination of relevant health information. The widespread uptake of social networking sites (SNS) presents a novel platform for public health promotion and management that can verily overcome the issues faced by current public health initiatives while reaching global populations of health consumers. This thesis aims to provide an exploratory analysis of the current landscape of health information communication across SNS, primarily through the platform Twitter. The research will address literature gaps in this cross-disciplinary field of health and communication sciences found for various SNS user-types, analyse and characterise the types of health information being disseminated across such platforms, as well as examine SNS activity during public health events. Public health officials and Web 2.0 platform developers can utilise findings from this thesis to address limitations of online public health-related communication insofar as they can assist with: a) advising plans for better engagement of information disseminated during health events; b) developing future applications and technologies that are appropriate for disadvantaged groups; c) identifying information dissemination strategies for authoritative health bodies and organizations to effectively reach populations

Searching with Tags: Do Tags Help Users Find Things?

This study examines the question of whether tags can be useful in the process of information retrieval. Participants searched a social bookmarking tool specialising in academic articles (CiteULike) and an online journal database (Pubmed). Participant actions were captured using screen capture software and they were asked to describe their search process. Users did make use of tags in their search process, as a guide to searching and as hyperlinks to potentially useful articles. However, users also made use of controlled vocabularies in the journal database to locate useful search terms and of links to related articles supplied by the database

Closing the loop: assisting archival appraisal and information retrieval in one sweep

In this article, we examine the similarities between the concept of appraisal, a process that takes place within the archives, and the concept of relevance judgement, a process fundamental to the evaluation of information retrieval systems. More specifically, we revisit selection criteria proposed as result of archival research, and work within the digital curation communities, and, compare them to relevance criteria as discussed within information retrieval's literature based discovery. We illustrate how closely these criteria relate to each other and discuss how understanding the relationships between the these disciplines could form a basis for proposing automated selection for archival processes and initiating multi-objective learning with respect to information retrieval

An Enhanced Web Data Learning Method for Integrating Item, Tag and Value for Mining Web Contents

The Proposed System Analyses the scopes introduced by Web 2.0 and collaborative tagging systems, several challenges have to be addressed too, notably, the problem of information overload. Recommender systems are among the most successful approaches for increasing the level of relevant content over the 201C;noise.201D; Traditional recommender systems fail to address the requirements presented in collaborative tagging systems. This paper considers the problem of item recommendation in collaborative tagging systems. It is proposed to model data from collaborative tagging systems with three-mode tensors, in order to capture the three-way correlations between users, tags, and items. By applying multiway analysis, latent correlations are revealed, which help to improve the quality of recommendations. Moreover, a hybrid scheme is proposed that additionally considers content-based information that is extracted from items. We propose an advanced data mining method using SVD that combines both tag and value similarity, item and user preference. SVD automatically extracts data from query result pages by first identifying and segmenting the query result records in the query result pages and then aligning the segmented query result records into a table, in which the data values from the same attribute are put into the same column. Specifically, we propose new techniques to handle the case when the query result records based on user preferences, which may be due to the presence of auxiliary information, such as a comment, recommendation or advertisement, and for handling any nested-structure that may exist in the query result records