Alternative mechanisms of discovering and accessing the economics literature

This study compares the bibliographic and full-text coverage of 15 conventional and alternative discovery/access mechanisms: two multidisciplinary library databases (Scopus and the Web of Science Core Collection), five single-subject databases, the integrated library search (ILS) mechanism of Manhattan University, a scholarly search engine (Google Scholar), two web-based scholarly databases (Dimensions and OpenAlex), two academic social networks (Academia.edu and ResearchGate), and two pirate sites (Anna's Archive and Sci-Hub). The analysis is based on known-item searches for 875 target documents in chemistry, materials science, cardiology, public health, economics, education, and psychology. Overall, Google Scholar, OpenAlex, and the ILS are the most comprehensive sources of bibliographic records. Google Scholar's coverage rate is higher than that of all the Manhattan University databases combined, and Scopus-the most comprehensive multidisciplinary library database-has a lower bibliographic coverage rate than Google Scholar, both of the web-based scholarly databases, one of the two ASNs, and one of the two pirate sites. In terms of full-text coverage, the best multidisciplinary options are the ILS, Google Scholar, and the two pirate sites. Although several of the alternative discovery/access mechanisms are deficient in terms of their user interfaces, search capabilities, and metadata, they nonetheless provide excellent bibliographic and full-text coverage of the scholarly literature. In contrast, many single-subject library databases provide very incomplete coverage of their own subject areas. These findings have implications for scholars and students as well as system-wide implications for the use, development, and evaluation of information resources.

This study investigates to know Myanmar academicians’ use of academic social networks, with especially focus on the Google scholar, Academia.edu and Researchgate. Adopting the descriptive survey design, the study used web based questionnaires as research instrument and were distributed among academicians in Arts and Science Universities in Myanmar. In total, 500 academicians filled in questionnaire were received back. The finding reveals that Myanmar academicians have knowledge of academic social networks. Google scholar is the most common used academic social network among Myanmar academicians. Academicians want to gain more new research area and researchers, but also more communicate with academic social network members for their academic works by joining academic social networks. Furthermore, academicians knew how to use academic social networks for their academic life. Academic social networks are recognized as important one for academicians and also academic social networks should be put into better research tool services.

Numerous issues arise in defining inequality: Inequality among whom? Inequality of what? And inequality over what time period? This paper is concerned with inequality among groups of individuals ov...

Introduction: In the history of the internet, social media occupy an exceptional place because they bring about sociological changes and cause things that will influence the course of history. It has become inevitable to conduct a study that examines the changes in the relationship between academic social networks and online patient-physician relationships, which have become widespread in recent years, especially among physicians. This study attempted to address this deficiency. Material and Method: An online survey was created on Google Forms that included questions about physicians' use of social and academic media networks and their communication habits with online patients. Age, gender, medical specialty and workplace, social media use, academic social networks usage, and relationships with patients via social media were analyzed. Results: Daily social media usage was significantly associated with age and medical specialty. Participants aged 40-50 and Basic Medic Science Consultants were least likely to use social media. The use of Facebook was the lowest among those under 30 (12.2%). Among those under 30, the use of LinkedIn was deficient (2.0%). Google Scholar was the most frequently used academic social network (38.5%). Surgical specialists were more likely to share medical content. Under 30 and over 50 were more likely to share their medical titles on social media than other groups. The percentage of those who reported having also physically examined the patient during online communication was 64.5%. This high rate is by no means negligible. Patients' most frequent responses to online communication requests were via WhatsApp (80.3%). The under-30 age group was found to have less contact with patients on social media. Conclusion: According to the results of the study, the use of the academic social network is lower than expected, even among academically active participants. The fact that Facebook usage is significantly lower among those under 30 suggests that Facebook is outdated as a social medium for young physicians. Participants in university hospitals, private clinics, and those under 40 use social media differently than other groups. More online patient communication is an important advance. It is also significant that the number of studies has increased after online communication. If investments are made in this topic, it can be expected that a substantial part of patient-doctor relationships will be handled online soon. However, social media studies wear out quickly, so they should be repeated frequently.

Social capital theory perspective on the role of academic social networking sites

PurposeThis brief note sheds light on the links between Journal of Economic Literature (JEL) codes and the Sustainable Development Goals (SDGs) of the United Nations.Design/methodology/approachThree alternative methods based on keyword overlap to establish links between SDGs and JEL codes are presented.FindingsThese simple linkages illustrate that the themes of SDGs have corresponding closely related JEL classification codes.Research limitations/implicationsThe mappings presented in this note are based on simple keyword overlap and are therefore necessarily imperfect and incomplete. There is plenty of room for further development.Practical implicationsDespite the demonstrated possibility of linking SDGs to existing JEL codes, introducing a specific JEL code for each SDG would reduce search costs for those searching for economic research related to specific SDGs.Originality/valueThe first and preliminary attempt to link SDGs and JEL codes.

Academic networks are expected to enhance scientific collaboration and thereby increase research outputs. However, little is known about whether and how the initial steps of getting to know other researchers translates into effective collaborations. In this paper, we investigate the evolution and co-evolution of an academic social network and a collaborative research network (using co-authorship as a proxy measure of the latter), and simultaneously examine the effect of individual researcher characteristics (e.g. gender, seniority or workplace) on their evolving relationships. We used longitudinal data from an international network in primary care cancer research: the CanTest Collaborative (CanTest). Surveys were distributed amongst CanTest researchers to map who knows who (the 'academic social network'). Co-authorship relations were derived from Scopus (the 'collaborative network'). Stochastic actor-oriented models were employed to investigate the evolution and co-evolution of both networks. Visualizing the development of the CanTest network revealed that researchers within CanTest get to know each other quickly and also start collaborating over time (evolution of the academic social network and collaborative network respectively). Results point to a stable and solid academic social network that is particularly encouraging towards more junior researchers; yet differing for male and female researchers (the effect of individual researcher characteristics). Moreover, although the academic social network and the research collaborations do not grow at the same pace, the benefit of creating academic social relationships to stimulate effective research collaboration is clearly demonstrated (co-evolution of both networks).

Academic networks are expected to enhance scientific collaboration and thereby increase research outputs. However, little is known about whether and how the initial steps of getting to know other researchers translates into effective collaborations. In this paper, we investigate the evolution and co-evolution of an academic social network and a collaborative research network (using co-authorship as a proxy measure of the latter), and simultaneously examine the effect of individual researcher characteristics (e.g. gender, seniority or workplace) on their evolving relationships. We used longitudinal data from an international network in primary care cancer research: the CanTest Collaborative (CanTest). Surveys were distributed amongst CanTest researchers to map who knows who (the ‘academic social network’). Co-authorship relations were derived from Scopus (the ‘collaborative network’). Stochastic actor-oriented models were employed to investigate the evolution and co-evolution of both networks. Visualizing the development of the CanTest network revealed that researchers within CanTest get to know each other quickly and also start collaborating over time (evolution of the academic social network and collaborative network respectively). Results point to a stable and solid academic social network that is particularly encouraging towards more junior researchers; yet differing for male and female researchers (the effect of individual researcher characteristics). Moreover, although the academic social network and the research collaborations do not grow at the same pace, the benefit of creating academic social relationships to stimulate effective research collaboration is clearly demonstrated (co-evolution of both networks).

The study investigated the use of Academic Social Networking Sites among Lecturers in State Universities in South East, Nigeria. The study adopted the descriptive surveydesign. Four (4) research questionsguided the study. The population of the study comprised 200Lecturersin the fiveStateUniversities spread across the fiveStates of South-East, Nigeria. The entire 200questionnaires wereadministered to the respondents;all were filled,returnedand used for the study because the entire population size was manageable. The major findings of the study were that Google Scholar and ResearchGate weremostly used by the Lecturer. Findings showed that the purpose of using Academic Social Networking Sitesis for Knowledge Sharing and Downloading of Articles. The reason Lecturers upload publications in the Academic Social Networking Sites arefor Citations, Information sharing and increasing of Views/Reads.The finding also revealed that majority of Lecturers access Academic Social Networking SitesMultiple times a day and also Daily.Based on the findings, it was recommended that Lecturers should explore other Academic Social Networking Sites due to their potentials in facilitating research activities, information sharing, collaboration among researchers, knowledge updates and so on

Information about faculty and their publications can be found in library databases such as the Library of Congress Name Authority File, VIAF, WorldCat, and institutional repositories; in identifier registries such as ORCID and ISNI; and on academic social networking sites such as Academia, Google Scholar, and ResearchGate, but the way search engines use such identifiers and profiles is unclear. Therefore, researchers at a large comprehensive university conducted several rounds of web searching before and after the creation and modification of faculty authority records. The sample consisted of 24 faculty and the 35 publications associated with their authorities. The researchers searched for the faculty and their publications on the social networking and identity websites directly, and then used Google, Bing, and Google Scholar to record which of the faculty members’ profiles and publications were found within the top 50 results. Faculty with more profiles were more visible in search engine results, and faculty with authority records ranked more highly in Google. Results related to publication discovery and ranking were more inconclusive, but revealed clear differences between search tools. The implications of this exploratory research can support educational efforts about academic identities and scholarly profiles, begin a research agenda, and inform methodological development surrounding the influence of identity records and academic social networking profiles on web visibility.

ABSTRACTWe construct a meta-ranking of 277 economics journals based on 22 different rankings. The ranking incorporates bibliometric indicators from four different databases (Web of Science, Scopus, Google Scholar, and RePEc). We account for the different scaling of the bibliometric indicators by standardizing each ranking score. We run a principal component analysis to assign weights to each ranking. In our meta-ranking, the top five journals are given by: Quarterly Journal of Economics, Journal of Financial Economics, Journal of Economic Literature (JEL), Journal of Finance, and Econometrica. Additionally, leaving out the JEL as a survey journal and the finance journals in our top 10 list we confirm the perceived top five journals in the economics profession.

The emergence of Academic Social Networks (ASNs) has provided opportunities for researchers to upload their publication work, discuss issues with an author, ask questions and build a connection between the researcher communities. With this large information available online, there is need of analyzing the information propagation in ASNs. In this paper, we analyzed the topic propagation in ASNs. We have used the popular academic search engine, Google Scholar for data collection and statistical software ‘R’ for data analysis. We used a scrapper collect the data set from Google Scholar and around 500 papers were examined to find the propagation of the current trend of topics in the specific domain. The result helps the novice researchers to choose the current trending topics and work on the issues in this topic.

Experiences affect mood, which in turn affects subsequent experiences. Recent studies suggest two specific principles. First, mood depends on how recent reward outcomes differ from expectations. Second, mood biases the way we perceive outcomes (e.g., rewards), and this bias affects learning about those outcomes. We propose that this two-way interaction serves to mitigate inefficiencies in the application of reinforcement learning to real-world problems. Specifically, we propose that mood represents the overall momentum of recent outcomes, and its biasing influence on the perception of outcomes ‘corrects’ learning to account for environmental dependencies. We describe potential dysfunctions of this adaptive mechanism that might contribute to the symptoms of mood disorders.

Academic social networks: Modeling, analysis, mining and applications

PurposeAs an important platform for academic communication and knowledge acquisition, academic social network (ASN) has attracted worldwide researchers. The purpose of this paper is to examine and compare the differences of corporation researchers in ASN utilization from the two aspects of social performance and academic performance.Design/methodology/approachApplying knowledge-based theory, this paper decoupled ASN into social network and academic network and measured utilization of users by social performance and academic performance. Hypotheses were proposed from the perspectives of research areas and corporate reputation. In the part of empirical research, the top 92 research corporations were selected as the sample, and relevant metric data from the member profile pages on ResearchGate was collected for comparing analysis to explore their utilization characteristics.FindingsThe results show that users of different research corporations have certain favoritism in their utilization of ASNs. Science and technology-oriented corporations are better in comprehensive social performance and academic quality. Science-oriented corporations are better at utilizing the interactive functions. However, neither social utilization nor academic utilization, technology-oriented corporations perform well.Originality/valueThis paper focuses on corporation researchers, who have started to embrace ASNs but whose behaviors were less studied. The research paradigm is an expansion and enrichment of the dual network decoupling theory in the field of ASN research. It also deepens the research on ASN utilization of corporation researchers and could give references for ASNs to improve service for corporation users in different research areas.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2019-0389