A View Of The Future Of Our Data

“Similarly, many well-intentioned advocates of open data failed to see how free information has always concentrated power in the owners of the fastest information-processing machines. Like the publishers of centuries past, the richest technology companies will always lead in extracting value from open data, giving them unearned leverage over the rest of society. So putting data into the public domain actually does precisely the opposite of leveling the playing field.

If individual data ownership is Scylla, the mythical sea monster who devoured unwary sailors, then open data is Charybdis, the whirlpool near Scylla’s cave. Finding the narrow path between the two means treating data like a police force or a water system — that is, as the subject of widely shared yet deeply responsible governance….”

How is science clicked on Twitter? Click metrics for Bitly short links to scientific publications – Fang – – Journal of the Association for Information Science and Technology – Wiley Online Library

Abstract:  To provide some context for the potential engagement behavior of Twitter users around science, this article investigates how Bitly short links to scientific publications embedded in scholarly Twitter mentions are clicked on Twitter. Based on the click metrics of over 1.1 million Bitly short links referring to Web of Science (WoS) publications, our results show that around 49.5% of them were not clicked by Twitter users. For those Bitly short links with clicks from Twitter, the majority of their Twitter clicks accumulated within a short period of time after they were first tweeted. Bitly short links to the publications in the field of Social Sciences and Humanities tend to attract more clicks from Twitter over other subject fields. This article also assesses the extent to which Twitter clicks are correlated with some other impact indicators. Twitter clicks are weakly correlated with scholarly impact indicators (WoS citations and Mendeley readers), but moderately correlated to other Twitter engagement indicators (total retweets and total likes). In light of these results, we highlight the importance of paying more attention to the click metrics of URLs in scholarly Twitter mentions, to improve our understanding about the more effective dissemination and reception of science information on Twitter.

 

How is science clicked on Twitter? Click metrics for Bitly short links to scientific publications – Fang – – Journal of the Association for Information Science and Technology – Wiley Online Library

Abstract:  To provide some context for the potential engagement behavior of Twitter users around science, this article investigates how Bitly short links to scientific publications embedded in scholarly Twitter mentions are clicked on Twitter. Based on the click metrics of over 1.1 million Bitly short links referring to Web of Science (WoS) publications, our results show that around 49.5% of them were not clicked by Twitter users. For those Bitly short links with clicks from Twitter, the majority of their Twitter clicks accumulated within a short period of time after they were first tweeted. Bitly short links to the publications in the field of Social Sciences and Humanities tend to attract more clicks from Twitter over other subject fields. This article also assesses the extent to which Twitter clicks are correlated with some other impact indicators. Twitter clicks are weakly correlated with scholarly impact indicators (WoS citations and Mendeley readers), but moderately correlated to other Twitter engagement indicators (total retweets and total likes). In light of these results, we highlight the importance of paying more attention to the click metrics of URLs in scholarly Twitter mentions, to improve our understanding about the more effective dissemination and reception of science information on Twitter.

 

How NARA’s Preserving More Than 20 Terabytes of Trump Social Media Data – Nextgov

“America’s federal records-keeper is in the midst of a hefty, ongoing effort to preserve many terabytes of digital and social media records from former President Donald Trump, who was suspended from using multiple online platforms in his final days in office.

To do so, the National Archives and Records Administration is leveraging a technology-based solution called ArchiveSocial.

“NARA has begun the task of working with ArchiveSocial to export the records from their platform and ingest them into NARA’s Electronic Records Archive for preservation,” a statement National Archives Public and Media Communications shared with Nextgov this week said. “We will also prepare exports from ArchiveSocial for public access, and they will be posted on trumplibrary.gov as they are made available.”…”

As new venues for peer review flower, will journals catch up? – Psychonomic Society Featured Content

“Given that preprints are here to stay, the field should be devoting resources to getting them certified more quickly as having received some amount of expert scrutiny. This is particularly important, of course, for preprints making claims relevant to the response to the pandemic.

In many cases, one component of this certification is already happening very quickly. More publicly-available peer review is happening today than ever before – just not at our journals. While academic journals typically call on half a handful of hand-picked, often reluctant referees, social media is not as limiting, and lively expert discussions are flourishing at forums like Twitter, Pubpeer, and the commenting facility of preprint servers.

So far, most journals have simply ignored this. As a result, science is now happening on two independent tracks, one slow, and one fast. The fast track is chaotic and unruly, while the slow track is bureaucratic and secretive – at most journals the experts’ comments never become available to readers, and the resulting evaluation by the editor of the strengths and weaknesses of the manuscript are never communicated to readers….

Will we need to reinvent the scientific journal wheel, or will legacy journals catch up with the modern world, by both taking advantage of and adding value to the peer review that is happening on the fast track?”

 

Sci-Hub Founder Criticises Sudden Twitter Ban Over Over “Counterfeit” Content * TorrentFreak

“Twitter has suspended the account of Sci-Hub, a site that offers a free gateway to paywalled research. The site is accused of violating the counterfeit policy of the social media platform. However, founder Alexandra Elbakyan believes that this is an effort to silence the growing support amidst a high profile court case in India.”

A communication strategy based on Twitter improves article citation rate and impact factor of medical journals – ScienceDirect

[Note even an abstract is OA.] 

“Medical journals use Twitter to optimise their visibility on the scientific community. It is by far the most used social media to share publications, since more than 20% of published articles receive at least one announcement on Twitter (compared to less than 5% of notifications on other social networks) [5] . It was initially described that, within a medical specialty, journals with a Twitter account have a higher impact factor than others and that the number of followers is correlated to the impact factor of the journal [67] . Several observational works showed that the announcement of a medical article publication on Twitter was strongly associated with its citation rate in the following years 891011 . In 2015, among anaesthesia journals, journals with an active and influential Twitter account had an higher journal impact factor and a greater number of article citations than those not embracing social media [12] . A meta-analysis of July 2020 concluded that the presence of an article on social media was probably associated with a higher number of citations [13] . Finally, two randomised studies, published in 2020 and not included in this meta-analysis, also showed that, for a given journal, articles that benefited from exposure on Twitter were 1.5 to 9 times more cited in the year following publication than articles randomised in the “no tweeting” group [1415] 

The majority of these works have only been published very recently and the strategy for using Twitter to optimise the number of citations is now a challenge for all medical journals. Several retrospective studies have looked at the impact of the use of a social media communication strategy by medical journals. They have shown that the introduction of Twitter to communicate as part of this strategy was associated with a higher number of articles consulted, a higher number of citations and shorter delays in citation after publication [1617] . Two studies (including one on anaesthesia journals) showed that journals that used a Twitter account to communicate were more likely to increase their impact factor than those that did not [1218] . Some researchers even suggest that the dissemination of medical information through social media, allowing quick and easy access after the peer-review publication process, may supplant the classical academic medical literature in the future [19] . This evolution has led to the creation of a new type of Editor in several medical journal editorial boards: the social media Editor (sometimes with the creation of a “specialised social media team” to assist him or her) [20] . This medical Editor shares, across a range of social media platforms, new journal articles with the aim of improving dissemination of journal content. Thus, beyond the scientific interest of a given article, which determines its chances of being cited, there is currently a parallel Editorial work consisting in optimising the visibility on Twitter to increase the number of citations and improve the impact factor. Some authors also start to focus on the best techniques for using Twitter and on the best ways to tweet to optimise communication, for example during a medical congress [21] ….”

 

Sharing is caring: an analysis of #FOAMed Twitter posts during the COVID-19 pandemic | Postgraduate Medical Journal

Abstract:  Purpose Free Open Access Medical Education (FOAMed) is a worldwide social media movement designed to accelerate and democratise the sharing of medical knowledge. This study sought to investigate the content shared through FOAMed during the emerging COVID-19 pandemic.

Study design Tweets containing the #FOAMed hashtag posted during a 24-hour period in April 2020 were studied. Included tweets were analysed using the Wiig knowledge management cycle framework (building knowledge, holding knowledge, pooling knowledge and using knowledge).

Results 1379 tweets contained the #FOAMed hashtag, of which 265 met the inclusion criteria and were included in the analysis. Included tweets were posted from 208 distinct users, originated from each world continent and were in five different languages. Three overarching themes were identified: (1) signposting and appraising evidence and guidelines; (2) sharing specialist and technical advice; and (3) personal and social engagement. Among 12 subthemes within these groupings, 11 aligned to one of the four dimensions of the Wiig knowledge management cycle framework, and the other focused on building and managing social networks. Almost 40% of tweets related directly to COVID-19.

Conclusion #FOAMed tweets during the COVID-19 pandemic included a broad range of resources, advice and support. Despite the geographical, language and disciplinary variation of contributing users and the lack of organisational structure uniting them, this social media medical community has been able to construct, share and use emerging technical knowledge through a time of extraordinary challenge and uncertainty for the global medical community.

This article is made freely available for use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

[2011.11940] Preprints as accelerator of scholarly communication: An empirical analysis in Mathematics

Abstract:  In this study we analyse the key driving factors of preprints in enhancing scholarly communication. To this end we use four groups of metrics, one referring to scholarly communication and based on bibliometric indicators (Web of Science and Scopus citations), while the others reflect usage (usage counts in Web of Science), capture (Mendeley readers) and social media attention (Tweets). Hereby we measure two effects associated with preprint publishing: publication delay and impact. We define and use several indicators to assess the impact of journal articles with previous preprint versions in arXiv. In particular, the indicators measure several times characterizing the process of arXiv preprints publishing and the reviewing process of the journal versions, and the ageing patterns of citations to preprints. In addition, we compare the observed patterns between preprints and non-OA articles without any previous preprint versions in arXiv. We could observe that the “early-view” and “open-access” effects of preprints contribute to a measurable citation and readership advantage of preprints. Articles with preprint versions are more likely to be mentioned in social media and have shorter Altmetric attention delay. Usage and capture prove to have only moderate but stronger correlation with citations than Tweets. The different slopes of the regression lines between the different indicators reflect different order of magnitude of usage, capture and citation data.

 

[2011.09079] Do ‘altmetric mentions’ follow Power Laws? Evidence from social media mention data in Altmetric.com

Abstract:  Power laws are a characteristic distribution that are ubiquitous, in that they are found almost everywhere, in both natural as well as in man-made systems. They tend to emerge in large, connected and self-organizing systems, for example, scholarly publications. Citations to scientific papers have been found to follow a power law, i.e., the number of papers having a certain level of citation x are proportional to x raised to some negative power. The distributional character of altmetrics has not been studied yet as altmetrics are among the newest indicators related to scholarly publications. Here we select a data sample from the altmetrics aggregator this http URL containing records from the platforms Facebook, Twitter, News, Blogs, etc., and the composite variable Alt-score for the period 2016. The individual and the composite data series of ‘mentions’ on the various platforms are fit to a power law distribution, and the parameters and goodness of fit determined using least squares regression. The log-log plot of the data, ‘mentions’ vs. number of papers, falls on an approximately linear line, suggesting the plausibility of a power law distribution. The fit is not very good in all cases due to large fluctuations in the tail. We show that fit to the power law can be improved by truncating the data series to eliminate large fluctuations in the tail. We conclude that altmetric distributions also follow power laws with a fairly good fit over a wide range of values. More rigorous methods of determination may not be necessary at present.