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Social media platforms provide a source of information about events. However, this information may not be credible, and the distance between an information source and the event may impact on that credibility. Therefore, the purpose of this paper is to address an understanding of the relationship between sources, physical distance from that event and the impact on credibility in social media.

In this paper, the authors focus on the impact of location on the distribution of content sources (informativeness and source) for different events, and identify the semantic features of the sources and the content of different credibility levels.

The study found that source location impacts on the number of sources across different events. Location also impacts on the proportion of semantic features in social media content.

This study illustrated the influence of location on credibility in social media. The study provided an overview of the relationship between content types including semantic features, the source and event locations. However, the authors will include the findings of this study to build the credibility model in the future research.

The results of this study provide a new understanding of reasons behind the overestimation problem in current credibility models when applied to different domains: such models need to be trained on data from the same place of event, as that can make the model more stable.

This study investigates several events – including crisis, politics and entertainment – with steady methodology. This gives new insights about the distribution of sources, credibility and other information types within and outside the country of an event. Also, this study used the power of location to find alternative approaches to assess credibility in social media.

This paper draws attention to the value of a new generation of information servers as a tool for human communication. Section I introduces the notion that the Internet is heralding a new era in communications, where peoples of different age and background are able to communicate with each other without barriers of distance or time. Section 2 examines the client‐server architecture which, together with the advent of graphic user interfaces, made possible a new generation of distributed, platform‐independent information servers. Four of the new generation servers are discussed in the remaining sections, namely Archie, gopher, WAIS and the World Wide Web, as well as video‐conferencing with CU‐seeMe.

This paper presents adaptations and tests undertaken to allow an information retrieval (IR) system to forecast the likelihood of avalanches on a particular day. The forecasting process uses historical data of the weather and avalanche conditions for a large number of days. A method for adapting these data into a form usable by a text‐based IR system is first described, followed by tests showing the resulting system’s accuracy to be equal to existing ‘custom built’ forecasting systems. From this, it is concluded that the adaptation methodology is effective at allowing such data to be used in a text‐based IR system. A number of advantages in using an IR system for avalanche forecasting are also presented.

This paper aims to report the results of a study investigating the relevance criteria used by health care professionals when seeking medical images.

Data were collected from 29 participants using a think‐aloud protocol and face‐to‐face interviews and analysed using the Straussian version of grounded theory (GT).

The results show that participants made use of 15 relevance criteria, although they agreed on topicality being the most important. The findings suggest that users apply different criteria in different situations when evaluating the relevancy of medical images.

To the best of the authors' knowledge, there have been few studies that investigate relevance judgments for visually orientated documents. Thus, this study helps to contribute to the understanding of medical image resources and the information needs of health care professionals. A clear understanding of the medical image information needs of health care professionals is also vital to the design process and development of medical image retrieval systems.

The purpose of this paper is to investigate how healthcare professionals search for and select the medical images they need within medical settings.

In total, 29 healthcare professionals participated in the study. Using a think‐aloud technique and face‐to‐face interviews, the authors asked participants to explain how they looked for medical images and how they judged the relevancy of retrieved images.

A total of 15 criteria were applied by participants when determining the relevance of medical images in relation to their information needs. Topicality was found to be the primary and most important criterion used by participants.

This study compares the relevance criteria used for medical images with those identified in the literature and highlights six additional criteria that have not been suggested in previous work.

Medicine is heavily dependent on images and health care professionals use medical images for clinical, educational and research purposes. This paper aims to investigate the resources used by health care professionals while searching for medical images.

The research is based on a qualitative study that uses the Straussian version of grounded theory and involved 29 health care professionals from various health and biomedical departments working within Sheffield Teaching Hospitals NHS (National Health Service) Foundation Trust. Data collection was carried out using semi‐structured interviews and think‐aloud protocols.

The findings show that health care professionals seek medical images in a variety of visual information sources, including those found online and from published medical literature. The research also identified a number of difficulties that health care professionals face when searching for medical images in various image resources.

There have been few studies that investigated the image resources used by health care professionals. Thus, this study contributes to the understanding of medical image resources and information needs of health care professionals. A clear understanding of the medical image information needs of health care professionals is also vital to the design process and development of medical image retrieval systems.

Dirk Ahlers studied computer science at the Carl-von-Ossietzky-University Oldenburg, Germany. In 2005, he started working as a research assistant at the OFFIS Institute for Information Technology, Oldenburg where he conducted projects in mobility and geospatial retrieval. While working at OFFIS, he also pursued his PhD with a topic in geographic information retrieval. He is currently working at UNITEC, a private university in Tegucigalpa, Honduras where he researches potential for local search for the case of a country with little Web coverage, challenging informal address schemes, and uncertain location data. His research interests are geospatial Web information retrieval, search engines, location-based services, Web technology, mobility, and everything geo. E-mail: dirk@dhere.de