Background: Micro-blogging services empower health institutions to quickly disseminate health information to many users. By analysing user data, infodemiology (i.e. improving public health using user contributed health related content) can be measured in terms of information diffusion. Objectives: Tweets by the WHO were examined in order to identify tweet attributes that lead to a high information diffusion rate using Twitter data collected between November 2019 and January 2020. Methods: One thousand hundred and seventy-seven tweets were collected using Python's Tweepy library. Afterwards, k-means clustering and manual coding were used to classify tweets by theme, sentiment, length and count of emojis, pictures, videos and links. Resulting groups with different characteristics were analysed for significant differences using Mann-Whitney U-and Kruskal-Wallis H-tests.
Results:The topic of the tweet, the included links, emojis and (one) picture as well as the tweet length significantly affected the tweets' diffusion, whereas sentiment and videos did not show any significant influence on the diffusion of tweets. Discussion: The findings of this study give insights on why specific health topics might generate less attention and do not showcase sufficient information diffusion.
Conclusion:The subject and appearance of a tweet influence its diffusion, making the design equally essential to the preparation of its content.
Image indexing and knowledge representation on Instagram are organized by folksonomy-oriented hashtags. What kinds of hashtags do Instagram users apply for different picture categories? We distinguish between food, pets, selfies, friends, activity, art, fashion, quotes (captioned photos), landscape and architecture as image categories, as well as content-related (ofness, aboutness, iconology), emotiveness, isness, performativeness, fakeness, "Insta"-tags and sentences as hashtag categories. Are there any differences in relative frequencies of hashtags in the image categories? What hashtag categories dominate users' indexing activities? Given an image category, what is the distribution of hashtag categories? Given a hashtag category, what is the distribution of image categories? We analyzed 1,000 pictures on Instagram with all-in-all 14,649 hashtags deploying content analysis.
The h-index is a widely used scientometric indicator on the researcher level working with a simple combination of publication and citation counts. In this article, we pursue two goals, namely the collection of empirical data about researchers’ personal estimations of the importance of the h-index for themselves as well as for their academic disciplines, and on the researchers’ concrete knowledge on the h-index and the way of its calculation. We worked with an online survey (including a knowledge test on the calculation of the h-index), which was finished by 1081 German university professors. We distinguished between the results for all participants, and, additionally, the results by gender, generation, and field of knowledge. We found a clear binary division between the academic knowledge fields: For the sciences and medicine the h-index is important for the researchers themselves and for their disciplines, while for the humanities and social sciences, economics, and law the h-index is considerably less important. Two fifths of the professors do not know details on the h-index or wrongly deem to know what the h-index is and failed our test. The researchers’ knowledge on the h-index is much smaller in the academic branches of the humanities and the social sciences. As the h-index is important for many researchers and as not all researchers are very knowledgeable about this author-specific indicator, it seems to be necessary to make researchers more aware of scholarly metrics literacy.
Abstract:A truebounded publication list of a scientific author consists of exactly all publications that meet two criteria: (1) they are formally published (e.g., journal article or proceeding paper); (2) they have scientific, scholarly, or academic content. A publication list is overbounded if it includes documents which do not meet the two criteria (such as novels); a publication list is underbounded if it is incomplete. Are authors' personal publication lists, found on their personal sites on the Internet or in institutional repositories, truebounded, overbounded, or underbounded? And are the respective publication lists generated through bibliographic information services truebounded, overbounded, or underbounded? As case studies, publications of nine International Society of Scientometrics and Informetrics (ISSI) Committee members (published between 2007 and 2016) were collected to create preferably complete personal publication lists according to the two criteria. We connect the "relative visibility of an author" with the concepts of truebounded, overbounded, and underbounded publication lists. The authors' relative visibility values were determined for the information services Web of Science (WoS), Scopus, and Google Scholar and compared to the relative visibility of the authors' personal publication lists. All results of the bibliographic information services are underbounded. Relative visibility is highest in Google Scholar, followed by Scopus and WoS.
Zusammenfassung
Über eine szientometrische Erfassung der Titelterme der Publikationen gibt der Artikel einen Überblick zu den aktuellen Forschungsthemen des Instituts für Informationswissenschaft und Wirtschaftsinformatik der Karl-Franzens-Universität Graz sowie der Abteilung für Informationswissenschaft der Heinrich-Heine-Universität Düsseldorf. Für die Erscheinungsjahrgänge 2010 bis 2016 konnten 129 Publikationen aus Graz und 249 aus Düsseldorf identifiziert werden. Top-Themen in Graz sind Informationswissenschaft, Österreich, mobile Systeme, Kommunikation, Universität, Zitation und (wissenschaftliche) Zeitschrift; in Düsseldorf dominieren Informationskompetenz, Informationswissenschaft, Social Media, informationelle (smarte) Städte und Wissen.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.