pinecone/core-2020-05-10-deduplication huggingface dataset:
Academia.edu: Social network or Academic Network?

Academic social network sites Academia.edu and ResearchGate, and reference sharing sites Mendeley, Bibsonomy, Zotero, and CiteULike, give scholars the ability to publicize their research outputs and connect with each other. With millions of users, these are a significant addition to the scholarly communication and academic information‐seeking eco‐structure. There is thus a need to understand the role that they play and the changes, if any, that they can make to the dynamics of academic careers. This article investigates attributes of philosophy scholars on Academia.edu, introducing a median‐based, time‐normalizing method to adjust for time delays in joining the site. In comparison to students, faculty tend to attract more profile views but female philosophers did not attract more profile views than did males, suggesting that academic capital drives philosophy uses of the site more than does friendship and networking. Secondary analyses of law, history, and computer science confirmed the faculty advantage (in terms of higher profile views) except for females in law and females in computer science. There was also a female advantage for both faculty and students in law and computer science as well as for history students. Hence, Academia.edu overall seems to reflect a hybrid of scholarly norms (the faculty advantage) and a female advantage that is suggestive of general social networking norms. Finally, traditional bibliometric measures did not correlate with any Academia.edu metrics for philosophers, perhaps because more senior academics use the site less extensively or because of the range informal scholarly activities that cannot be measured by bibliometric methods.This paper is supported by ACUMEN (Academic Careers Understood through Measurement and Norms) project, grant agreement number 266632, under the Seventh Framework Program of the European Union
Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine
Disseminating research with web CV hyperlinks

Some curricula vitae (web CVs) of academics on the web, including homepages and publication lists, link to open‐access (OA) articles, resources, abstracts in publishers' websites, or academic discussions, helping to disseminate research. To assess how common such practices are and whether they vary by discipline, gender, and country, the authors conducted a large‐scale e‐mail survey of astronomy and astrophysics, public health, environmental engineering, and philosophy across 15 European countries and analyzed hyperlinks from web CVs of academics. About 60% of the 2,154 survey responses reported having a web CV or something similar, and there were differences between disciplines, genders, and countries. A follow‐up outlink analysis of 2,700 web CVs found that a third had at least one outlink to an OA target, typically a public eprint archive or an individual self‐archived file. This proportion was considerably higher in astronomy (48%) and philosophy (37%) than in environmental engineering (29%) and public health (21%). There were also differences in linking to publishers' websites, resources, and discussions. Perhaps most important, however, the amount of linking to OA publications seems to be much lower than allowed by publishers and journals, suggesting that many opportunities for disseminating full‐text research online are being missed, especially in disciplines without established repositories. Moreover, few academics seem to be exploiting their CVs to link to discussions, resources, or article abstracts, which seems to be another missed opportunity for publicizing research
Mapping the Asymmetrical Citation Relationships Between Journals by h-Plots

I propose the use of h-plots for visualizing the asymmetric relationships between the citing and cited profiles of journals in a common map. With this exploratory tool, we can understand better the journal's dual roles of citing and being cited in a reference network. The h-plot is introduced and its use is validated with a set of 25 journals belonging to the statistics area. The relatedness factor is considered for describing the relations of citations from a journal “i” to a journal “j,” and the citations from the journal “j” to the journal “i.” More information has been extracted from the h-plot, compared with other statistical techniques for modelling and representing asymmetric data, such as multidimensional unfolding
Scientific journals in Brazil and Spain: Alternative publishing models

This paper describes high-quality journals in Brazil and Spain, with an emphasis on the distribution models used. It presents the general characteristics (age, type of publisher, and theme) and analyzes the distribution model by studying the type of format (print or digital), the type of access (open access or subscription), and the technology platform used. The 549 journals analyzed (249 in Brazil and 300 in Spain) are included in the 2011 Web of Science (WoS) and Scopus databases. Data on each journal were collected directly from their websites between March and October 2012. Brazil has a fully open access distribution model (97%) in which few journals require payment by authors thanks to cultural, financial, operational, and technological support provided by public agencies. In Spain, open access journals account for 55% of the total and have also received support from public agencies, although to a lesser extent. These results show that there are systems support of open access in scientific journals other than the"author pays" model advocated by the Finch report for the United Kingdom
An automatic method for extracting citations from Google Books

Recent studies have shown that counting citations from books can help scholarly impact assessment and that Google Books (GB) is a useful source of such citation counts, despite its lack of a public citation index. Searching GB for citations produces approximate matches, however, and so its raw results need time‐consuming human filtering. In response, this article introduces a method to automatically remove false and irrelevant matches from GB citation searches in addition to introducing refinements to a previous GB manual citation extraction method. The method was evaluated by manual checking of sampled GB results and comparing citations to about 14,500 monographs in the Thomson Reuters Book Citation Index (BKCI) against automatically extracted citations from GB across 24 subject areas. GB citations were 103% to 137% as numerous as BKCI citations in the humanities, except for tourism (72%) and linguistics (91%), 46% to 85% in social sciences, but only 8% to 53% in the sciences. In all cases, however, GB had substantially more citing books than did BKCI, with BKCI's results coming predominantly from journal articles. Moderate correlations between the GB and BKCI citation counts in social sciences and humanities, with most BKCI results coming from journal articles rather than books, suggests that they could measure the different aspects of impact, however.University of Wolverhampto
"Making my own luck": Serendipity strategies and how to support them in digital information environments

Serendipity occurs when unexpected circumstances and an 'aha' moment of insight result in a valuable, unanticipated outcome. Designing digital information environments to support serendipity can not only provide users with new knowledge, but also propel them in exciting directions they might not otherwise have travelled in - surprising and delighting them along the way. As serendipity involves unexpected circumstances it cannot be directly controlled, but it can potentially be influenced. However, to the best of our knowledge, no previous work has focused on providing a rich empirical understanding of how it might be influenced. We interviewed 14 creative professionals to identify their self-reported strategies aimed at increasing the likelihood of serendipity. These strategies form a framework for examining ways existing digital environments support serendipity and for considering how future environments can create opportunities for it. This is a new way of thinking about how to design for serendipity; by supporting the strategies found to increase its likelihood rather than attempting to support serendipity as a discrete phenomenon, digital environments not only have the potential to help users experience serendipity but also encourage them to adopt the strategies necessary to experience it more often
Information seeking, use, and decision making

YesIn this paper we explored three areas: decision making and information seeking, the relationship between information seeking and uncertainty, and the role of expertise in influencing information use. This was undertaken in the context of a qualitative study into decision making in the initial stages of emergency response to major incidents. The research took an interpretive approach in which activity theory is used as an analytical framework. The research provides further evidence that the context of the activity and individual differences influence the choice of decision mode and associated information behavior. We also established that information is often not used to resolve uncertainty in decision making and indeed information is often sought and used after the decision is made to justify the decision. Finally, we point to the significance of both expertise and confidence in understanding information behavior. The contribution of the research to existing theoretical frameworks is discussed and a modified version of Wilson's problem-solving model is proposed
Factors affecting citation rates of research articles

This study examines whether there are some general trends across subject fields regarding the factors affecting the number of citations of articles, focusing especially on those factors that are not directly related to the quality or content of articles (extrinsic factors). For this purpose, from 6 selected subject fields (condensed matter physics, inorganic and nuclear chemistry, electric and electronic engineering, biochemistry and molecular biology, physiology, and gastroenterology), original articles published in the same year were sampled (n = 230–240 for each field). Then, the citation counts received by the articles in relatively long citation windows (6 and 11 years after publication) were predicted by negative binomial multiple regression (NBMR) analysis for each field. Various article features about author collaboration, cited references, visibility, authors\u27 achievements (measured by past publications and citedness), and publishing journals were considered as the explanatory variables of NBMR. Some generality across the fields was found with regard to the selected predicting factors and the degree of significance of these predictors. The Price index was the strongest predictor of citations, and number of references was the next. The effects of number of authors and authors\u27 achievement measures were rather weak
User participation in an academic social networking service: A survey of open group users on Mendeley

© 2014 ASIS & T. Although there are a number of social networking services that specifically target scholars, little has been published about the actual practices and the usage of these so-called academic social networking services (ASNSs). To fill this gap, we explore the populations of academics who engage in social activities using an ASNS; as an indicator of further engagement, we also determine their various motivations for joining a group in ASNSs. Using groups and their members in Mendeley as the platform for our case study, we obtained 146 participant responses from our online survey about users' common activities, usage habits, and motivations for joining groups. Our results show that (a) participants did not engage with social-based features as frequently and actively as they engaged with research-based features, and (b) users who joined more groups seemed to have a stronger motivation to increase their professional visibility and to contribute the research articles that they had read to the group reading list. Our results generate interesting insights into Mendeley's user populations, their activities, and their motivations relative to the social features of Mendeley. We also argue that further design of ASNSs is needed to take greater account of disciplinary differences in scholarly communication and to establish incentive mechanisms for encouraging user participation
A Study of the Role of Visual Information in Supporting Ideation in Graphic Design

Existing computer technologies poorly support the ideation phase common to graphic design practice. Finding and indexing visual material to assist the process of ideation often fall on the designer, leading to user experiences that are less than ideal. To inform development of computer systems to assist graphic designers in the ideation phase of the design process, we conducted interviews with 15 professional graphic designers about their design process and visual information needs. Based on the study, we propose a set of requirements for an ideation-support system for graphic design
A new type of misconduct in the field of the Physical Sciences: the case
  of the pseudonyms used by I. Ciufolini to anonymously criticize other
  people's works on arXiv

The above article, published online on 28 April 2014 in Wiley Online Library
(wileyonlinelibrary.com), has been withdrawn with agreement from the journal
Editor-in-Chief, Blaise Cronin, and Wiley Periodicals, Inc. The withdrawal has
been agreed for legal reasons.Comment: LaTex2e, 3 pages, no figures, no tables, 3 references. After having
  been accepted on 5 January 2014 by the Editor-in-Chief of the Journal of the
  Association for Information Science and Technology as "Special accept
  (without external review)", it has been withdrawn for "legal reasons" without
  new factual evidence contradicting its conten
Who Publishes in “Predatory” Journals?

Many open access journals have a reputation for being of low quality and being dishonest with regard to peer review and publishing costs. Such journals are labeled “predatory” journals. This study examines author profiles for some of these “predatory” journals as well as for groups of more well-recognized open access journals. We collect and analyze the publication record, citation count, and geographic location of authors from the various groups of journals. Statistical analyses verify that each group of journals has a distinct author population. Those who publish in “predatory” journals are, for the most part, young and inexperienced researchers from developing countries. We believe that economic and sociocultural conditions in these developing countries have contributed to the differences found in authorship between “predatory” and “nonpredatory” journals
How everyday language can and will boost effective information retrieval

Typing 2 or 3 keywords into a browser has become an easy and efficient way to find information. Yet, typing even short queries becomes tedious on ever shrinking (virtual) keyboards. Meanwhile, speech processing is maturing rapidly, facilitating everyday language input. Also, wearable technology can inform users proactively by listening in on their conversations or processing their social media interactions. Given these developments, everyday language may soon become the new input of choice.\ud
\ud
\ud
We present an information retrieval (IR) algorithm specifically designed to accept everyday language. It integrates two paradigms of information retrieval, previously studied in isolation; one directed mainly at the surface structure of language, the other primarily at the underlying meaning.\ud
\ud
\ud
The integration was achieved by a Markov machine that encodes meaning by its transition graph, and surface structure by the language it generates. A rigorous evaluation of the approach showed, first, that it can compete with the quality of existing language models, second, that it is more effective the more verbose the input, and third, as a consequence, that it is promising for an imminent transition from keyword input, where the onus is on the user to formulate concise queries, to a modality where users can express more freely, more informal, and more natural their need for information in everyday language
Does research output cause economic growth or vice versa? Evidence from 34 OECD countries

The causal relation between research and economic growth is of particular
importance for political support of science and technology as well as for academic purposes.
This paper revisits the causal relationship between research papers published and economic
growth in OECD countries for the period 1981-2011, using bootstrap panel causality analysis,
which accounts for cross-section dependency and heterogeneity across countries. Our empirical
results support unidirectional causality running from research output (in terms of total number
of papers published) to economic growth for the US, Finland, Hungary, and Mexico; the
opposite causality from economic growth to research papers published for Canada, France,
Italy, New Zealand, UK, Austria, Israel, and Poland; and no causality for the rest of the
countries. Our findings provide important policy implications for research policies and
strategies for OECD countries.http://www.asis.org/jasist.htmlhb201
The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags

© 2014 ASIS & T. Crowdsourcing has emerged as a way to harvest social wisdom from thousands of volunteers to perform a series of tasks online. However, little research has been devoted to exploring the impact of various factors such as the content of a resource or crowdsourcing interface design on user tagging behavior. Although images' titles and descriptions are frequently available in image digital libraries, it is not clear whether they should be displayed to crowdworkers engaged in tagging. This paper focuses on offering insight to the curators of digital image libraries who face this dilemma by examining (i) how descriptions influence the user in his/her tagging behavior and (ii) how this relates to the (a) nature of the tags, (b) the emergent folksonomy, and (c) the findability of the images in the tagging system. We compared two different methods for collecting image tags from Amazon's Mechanical Turk's crowdworkers - with and without image descriptions. Several properties of generated tags were examined from different perspectives: diversity, specificity, reusability, quality, similarity, descriptiveness, and so on. In addition, the study was carried out to examine the impact of image description on supporting users' information seeking with a tag cloud interface. The results showed that the properties of tags are affected by the crowdsourcing approach. Tags from the "with description" condition are more diverse and more specific than tags from the "without description" condition, while the latter has a higher tag reuse rate. A user study also revealed that different tag sets provided different support for search. Tags produced "with description" shortened the path to the target results, whereas tags produced without description increased user success in the search task
Analysis of biomedical and health queries: Lessons learned from TREC and CLEF evaluation benchmarks

A large body of research work examined, from both the query side and the user behaviour side, the characteristics of medical and health-related searches. One of the core issues in medical information retrieval is diversity of tasks that lead to diversity of categories of information needs and queries. From the evaluation perspective, another related challenging issue is the limited availability of appropriate test collections allowing the experimental validation of medically task oriented IR techniques and systems. Since 2003, medical standardized evaluation benchmarks such as TREC and CLEF provide to information retrieval research community various controlled medical tasks specifications with related document collections, queries, relevance assessment and specific metadata. The literature clearly reports a rapid increase in the use of these evaluation benchmarks. In this paper, we explore the peculiarities of TREC and CLEF medically oriented tasks and queries through the analysis of the differences and the similarities between queries across tasks, with respect to length, specificity and clarity features and then study their effect on retrieval performance. More specifically, we developed an exploratory data analysis as well as a predictive data analysis using 11 TREC and CLEF medical test collections containing 374 queries and their corresponding document collections and expert relevance assessments, organized according to the involved medical tasks. Based on the outcome of our study, we show that, even for expert oriented queries, language specificity level varies significantly across tasks as well as search difficulty and that the most related predictive factors are linked to query length and query clarity. Additional findings highlight that query clarity factors are task dependent and that query terms specificity based on domain-specific terminology resources is not significantly linked to term rareness in the document collection. The lessons learned from our study could serve as starting points for the design of future task-based medical IR frameworks
Data Journals: A Survey

Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms such as data deluge and big data today characterize numerous (research) initiatives, much work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, and quality issues to a rather general lack of a data-sharing culture. Lately, data journals have overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for data set description, availability, citation, quality, and open access. We close by identifying ways to expand and strengthen the data journals approach as a means to promote data set access and exploitation