Characteristics of LIS Research Articles Affecting Their Citation Impact

The paper analyses the citation impact of Library and Information Science, LIS for short, research articles published in 31 leading international LIS journals in 2015. The main research question is: to what degree do authors' disciplinary composition in association with other content characteristics of LIS articles affect their citation impact? The impact is analysed in terms of the number of citations received and their authority, using outlier normalization and subfield normalization. The article characteristics analysed using quantitative content analysis include topic, methodology, type of contribution, and the disciplinary composition of their author teams. The citations received by the articles are traced from 2015 to May 2021. Citing document authority is measured by the citations they had received up to May 2021. The overall finding was that authors' disciplinary composition is significantly associated with citation scores. The differences in citation scores between disciplinary compositions appeared typically within information retrieval and scientific communication. In both topics LIS and computer science jointly received significantly higher citation scores than many disciplines like LIS alone or humanities in information retrieval, or natural sciences, medicine, or social sciences alone in scientific communication. The paper is original in allowing joint analysis of content, authorship composition, and impact.Comment: 30 pages, 4 figure

On conceptual models for information seeking and retrieval research

There are several kinds of conceptual models for information seeking and retrieval (IS&R). The paper suggests that some models are of a summary type and others more analytic. Such models serve different research purposes. The purpose of this paper is to discuss the functions of conceptual models in scientific research, in IS&R research in particular. What kind of models are there and in what ways may they help the investigators? What kinds of models are needed for various purposes? In particular, we are looking for models that provide guidance in setting research questions, and formulation of hypotheses. As a example, the paper discusses [at length] one analytical model of task-based information seeking and its contribution to the development of the research area

An Information Nutritional Label for Online Documents

International audienceWith the proliferation of online information sources, it has become more and more difficult to judge the trustworthiness of news found on the Web. The beauty of the web is its openness, but this openness has lead to a proliferation of false and unreliable information, whose presentation makes it difficult to detect. It may be impossible to detect what is “real news” and what is “fake news” since this discussion ultimately leads to a deep philosophical discussion of what is true and what is false. However, recent advances in natural language processing allow us to analyze information objectively according to certain objective criteria (for example, the number of spelling errors). Here we propose creating an “information nutrition label” that we can automatically generated for any online text. Among others, the label provides information on the following computable criteria: factuality, virality, opinion, controversy, authority, technicality, and topicality. With this label, we hope to help readers make more informed judgments about the items they read

Frontiers, Challenges, and Opportunities for Information Retrieval – Report from SWIRL 2012, The Second Strategic Workshop on Information Retrieval in Lorne

During a three-day workshop in February 2012, 45 Information Retrieval researchers met to discuss long-range challenges and opportunities within the field. The result of the workshop is a diverse set of research directions, project ideas, and challenge areas. This report describes the workshop format, provides summaries of broad themes that emerged, includes brief descriptions of all the ideas, and provides detailed discussion of six proposals that were voted "most interesting" by the participants. Key themes include the need to: move beyond ranked lists of documents to support richer dialog and presentation, represent the context of search and searchers, provide richer support for information seeking, enable retrieval of a wide range of structured and unstructured content, and develop new evaluation methodologies.QC 20130129</p