Hi Bluesky!
Wenceslao Arroyo Machado
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Just published the preprint 'The Botization of Science? Large-scale study of the presence and impact of Twitter bots in science dissemination' 🤖
We aim to answer the classic question: Do #Twitter bots interfere with #altmetrics? For this purpose, we conducted the first large-scale study on the presence of bots disseminating papers and their impact on altmetrics. Our results show an uneven activity and influence.
📝 Preprint: https://doi.org/10.48550/arXiv.2310.12741
💾 Bots dataset: https://doi.org/10.5281/zenodo.8075234
The Botization of Science? Large-scale study of the presence and impact of Twitter bots in science dissemination
Twitter bots are a controversial element of the platform, and their negative impact is well known. In the field of scientific communication, they have been perceived in a more positive light, and the accounts that serve as feeds alerting about scientific publications are quite common. However, despite being aware of the presence of bots in the dissemination of science, no large-scale estimations have been made nor has it been evaluated if they can truly interfere with altmetrics. Analyzing a dataset of 3,744,231 papers published between 2017 and 2021 and their associated 51,230,936 Twitter mentions, our goal was to determine the volume of publications mentioned by bots and whether they skew altmetrics indicators. Using the BotometerLite API, we categorized Twitter accounts based on their likelihood of being bots. The results showed that 11,073 accounts (0.23% of total users) exhibited automated behavior, contributing to 4.72% of all mentions. A significant bias was observed in the activity of bots. Their presence was particularly pronounced in disciplines such as Mathematics, Physics, and Space Sciences, with some specialties even exceeding 70% of the tweets. However, these are extreme cases, and the impact of this activity on altmetrics varies by speciality, with minimal influence in Arts & Humanities and Social Sciences. This research emphasizes the importance of distinguishing between specialties and disciplines when using Twitter as an altmetric.
Leiden MadtricsIn our latest blog post, @Wences and @rodrigocostas discuss the study of science on Wikipedia and its use in scientometric research @cwts https://www.leidenmadtrics.nl/articles/five-key-facts-to-consider-when-studying-science-on-wikipedia
Five key facts to consider when studying science on Wikipedia
The presence of science on Wikipedia is a recurrent research topic in the scientometric community. However, its full potential for the study of science-society relations has not yet been fully explored. These are some of the key facts to be considered when studying it.
We have just published in the @QSS_ISSI the paper we have been working on for some time exploring the #informetric possibilities of #Wikipeda (with @[email protected] and @rodrigocostas1).
One of the main results of this work is a comprehensive open dataset 🔓 of the English Wikipedia with many metrics of each page, other entities, and the relationships between all of them #opendata #openscience
Paper: 
Wikinformetrics: Construction and description of an open Wikipedia knowledge graph dataset for informetric purposes
Abstract. Wikipedia is one of the most visited websites in the world and is also a frequent subject of scientific research. However, the analytical possibilities of Wikipedia information have not yet been analyzed considering at the same time both a large volume of pages and attributes. The main objective of this work is to offer a methodological framework and an open knowledge graph for the informetric large-scale study of Wikipedia. Features of Wikipedia pages are compared with those of scientific publications to highlight the (di)similarities between the two types of documents. Based on this comparison, different analytical possibilities that Wikipedia and its various data sources offer are explored, ultimately offering a set of metrics meant to study Wikipedia from different analytical dimensions. In parallel, a complete dedicated dataset of the English Wikipedia was built (and shared) following a relational model. Finally, a descriptive case study is carried out on the English Wikipedia dataset to illustrate the analytical potential of the knowledge graph and its metrics.Peer Review. https://publons.com/publon/10.1162/qss_a_00226
Vincent TraagIs Wikipedia a news media or a historical encyclopedia? Of course both & none! Here we propose a framework to dissect this complex system to understand how Wikipedia bridges between news and history. Work w @[email protected] & @[email protected]. https://arxiv.org/pdf/2211.07616.pdf @[email protected]
🐦🔗: https://twitter.com/TahaYasseri/status/1592496143031709699
Taking a walk through the Fediverse 