Hashtags for Gatekeeping of Information on Social Media

Since the inception of gatekeeping research in the 1940s, most studies on gatekeeping have been human‐centric, treating and studying individuals as gatekeepers, who perform their gatekeeping role using a combination of the following mechanisms: forming communities, and/or broadcasting, discovering‐searching, collecting, organizing, or protecting information. However, the nature of communication channels and how information is produced by and shared with users has fundamentally changed in the last 80 years. One significant change is the growing use of technology‐enabled metadata like hashtags when sharing information on social media. Rarely any study investigates whether hashtags can perform gatekeeping of information and what it means for information gatekeeping. This paper fills in the gap by conducting a content analysis of 77 interdisciplinary studies on hashtags and gatekeeping to confirm how they can implement six gatekeeping mechanisms. This study shows that hashtags expand our understanding of the role of technology solutions in gatekeeping and advance research on hierarchical gatekeeping. The benefits of hashtags for gatekeeping suggest that they act as “information anchors” for online communities, thereby highlighting the utility of information gatekeepers for society

The Social Systems Citation Theory (SSCT): A proposal to use the social systems theory for conceptualizing publications and their citations links

The normative theory of citing considers citations as rewarding tools to acknowledge the influence of scientific works, while the social constructivist theory of citing considers citations, for example, as persuasion tools used by authors to support their claims, and convince the scientific community that those claims are valid. Other citation theories and models have been proposed in recent years to overcome the limitations of the normative and social constructivist theories. Nevertheless, they have not been able to fully explain all citation motives of scientists (but have a certain focus). This study proposes a new theory (which we call “social systems citation theory”, SSCT) that integrates previous theories and models on publications and their citation links and is mainly based on Niklas Luhmann’s “social systems theory”. Luhmann’s social systems theory focuses on “communications” as the basic constituting elements of a social science system and not on humans and their motives. Humans are not part of social systems but are connected with them and irritate them. Thus, the social systems theory does not have the problem of integrating various and different motives of humans to cite in the science system. In the SSCT, authors’ motives to cite belong to psychic systems while publications and their citation links belong to the social science system. The systems operate autonomously but interact with each other: the social system operates recursively with publications and citation links. Although psychic systems stimulate or irritate the science system, they do not determine communications in the science system. In this study, we explain the SSCT and demonstrate how the theory can be used to underlie empirical bibliometric studies

Evaluating the Meetings Output of Educational Council and Departments in School of Health Management and Information Sciences: Content Analysis of Minutes

Introduction: This study analyzes the minutes of departments and educational council in Tehran University of Medical Sciences, School of Health Management and Information Sciences and evaluates the strengths and weaknesses of the departments meetings. Methods: This was a descriptive study. The study population was all minutes of departments in School of Health Management and Information Sciences in TUMS in 2004-2010. Minutes were transformed into digital format with a scanner. We used NVivo 8 software to codify and analyze the data. Results: Findings showed that in the meetings of both educational council and departments more attention was paid to the “thesis and proposal” and “educational issues”. Furthermore, each department had its own unique subjects which were not discussed in other departments. Conclusion: The chancellor at this school, deputy of dean and head of departments can use findings of current study to know the weaknesses of departments meetings and plan for better organization of weekly and monthly meetings in order to achieve the school goals and serve students better

Altmetrics and societal impact measurements: Match or mismatch? A literature review

Can alternative metrics (altmetrics) data be used to measure societal impact? We wrote this literature overview of empirical studies in order to find an answer to this question. The overview includes two parts. The first part, “societal impact measurements”, explains possible methods and problems in measuring the societal impact of research, case studies for societal impact measurement, societal impact considerations at funding organizations, and the societal problems that should be solved by science. The second part of the review, “altmetrics”, addresses a major question in research evaluation, which is whether altmetrics are proper indicators for measuring the societal impact of research. In the second part we explain the data sources used for altmetrics studies and the importance of field-normalized indicators for impact measurements. This review indicates that it should be relevant for impact measurements to be oriented towards pressing societal problems. Case studies in which societal impact of certain pieces of research is explained seem to provide a legitimate method for measuring societal impact. In the use of altmetrics, field-specific differences should be considered by applying field normalization (in cross-field comparisons). Altmetrics data such as social media counts might mainly reflect the public interest and discussion of scholarly works rather than their societal impact. Altmetrics (Twitter data) might be especially fruitfully employed for research evaluation purposes, if they are used in the context of network approaches. Conclusions based on altmetrics data in research evaluation should be drawn with caution

#Metoo: People’s concerns, emotions, and shared information on Twitter

This study uses text mining to explore the tweets posted and shared by people regarding the #MeToo movement. We used the Twitter’s Application Programming Interface (API) to collect English language tweets that contained #MeToo or MeToo keywords. Using RStudio, 17956 tweets (re-tweets excluded) were retrieved and analyzed. The data was cleaned, tweets with more than 5 hashtags and screen names with multiple tweets were excluded, resulting in 10952 tweets. The most frequently shared words were #metoo (n=10701), women (n=2728), movement (n=1879), sexual (n=1330), harassment (n=818), rape (n=724), accused (n=717), don’t (n=678), people (635), and stand (n=510). The most frequent negative sentiments were harassment (n=638), rape (n=575), assault (n=280), abuse (n=239), afraid (n=212), uncomfortable (n=172), allegations (n=165), bad (n=136), hurts (n=136) and wrong (n=133). The top positive sentiments were support (n=223), love (n=119), powerful (n=86), golden (n=73), survivor (n=68), respect (64), safe (57), free (53), protect (53) and supporting (n=50). The network analysis of keywords with a correlation of higher than 0.6 demonstrated 5 clusters of keywords: {study, hurts, mentor, afraid, @nypost}, {#metoo, forces, legal, test}, {represent, caught, middle, accusers, unions}, {#fightfor15, standing, UK, workers, fighting}, and {teaching, consent, debate, kids}. Results demonstrated the major topics shared by people on Twitter regarding sexual harassment and the MeToo movement. For example, one cluster pointed to a recent study which indicated managers are afraid of mentoring women after the #MeToo movement

Evaluation of Medical Librarians’ Level of Information and Communication Technology Skills Based on MLA Statements: A study in Iran

Due to the importance of ICT skills, several leading associations have released guidelines on needed ICT skills for librarians. In this study, Medical Library Association (MLA) statements on ICT skills were used for evaluating medical librarians’ level of information and communication technology expertise in Iran. A census sampling method was used. Chief Librarians working in college libraries affiliated to the Ministry of Health and Medical Education (MOHME) in Iran participated in this study. Findings showed that based on MLA’s skill statements, medical LIS professionals working in medical, dental and pharmacy colleges possessed adequate skill in communications and information infrastructure including the Internet and Web; inadequate skill in integration of systems and technologies; and applications in emerging areas of biomedicine, computational biology and health information; medium skill in basic principles of automated systems, data standards, and system analysis techniques including design and evaluation; acquisition, use, and evaluation of information technologies; and technological solutions for permanent access to electronic information