Articles on Social Media Relating to Written Communication

• Loading metrics

Open up Access

Peer-reviewed

Research Article

Social media usage to share information in communication journals: An analysis of social media activity and article citations

Social media usage to share information in communication journals: An assay of social media action and article citations

• Yasemin Özkent

ten

• Published: February 9, 2022
• https://doi.org/10.1371/journal.pone.0263725

Figures

Abstract

Social media has surrounded every surface area of life, and social media platforms have go indispensable for today's communication. Many journals use social media actively to promote and disseminate new articles. Its utilise to share the articles contributes many benefits, such as reaching more people and spreading data faster. Withal, at that place is no consensus in the studies that to evaluate betwixt tweeted and non-tweeted papers regarding their commendation numbers. Therefore, information technology was aimed to prove the effect of social media on the citations of articles in the peak ten communication-based journals. For this purpose, this work evaluated original articles published in the top 10 communication journals in 2018. The top 10 communication-based journals were chosen based on SCImago Journal & Land Rank (cited in 2019). Afterwards, it was recorded the traditional commendation numbers (Google Scholar and Thompson-Reuters Spider web of Science) and social media exposure of the articles in January 2021 (about three years afterward the manufactures' publication appointment). Information technology was assumed that this period would let the impact of the published articles (the citations and Twitter mentions) to be fully observed. Based on this assessment, a positive correlation between exposure to social media and article citations was observed in this study.

Commendation: Özkent Y (2022) Social media usage to share information in advice journals: An analysis of social media action and article citations. PLoS 1 17(two): e0263725. https://doi.org/x.1371/journal.pone.0263725

Editor: Marcelo Hermes-Lima, Universidade de Brasilia, BRAZIL

Received: May 3, 2021; Accustomed: January 25, 2022; Published: February 9, 2022

Copyright: © 2022 Yasemin Özkent. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Information Availability: The information underlying the results presented in the written report are available from: https://github.com/yaseminozkent/minimal-information-set.git.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have alleged that no competing interests be.

Introduction

The social network has become a tool for bringing people together, allowing individuals to listing the users they are connected to, and to see other users' connections [1]. Social media platforms (blogs, social networking sites, microblogging, etc.) contain all Web 2.0-based services. Social media has surrounded every area of life, and social media platforms are indispensable for today'southward communication [2]. Scientists from various fields frequently use SoMe, especially Twitter, in almost of their professional activities [3].

Scientists often employ social media platforms to produce and debate ideas, share existent-time information, spread their enquiry, and discover collaborators [two, four]. The way information is collected, disseminated and consumed has been significantly inverse because social media past information technology is encompassing and easily accessible. There has been a significant increase in the number of studies related to social media with an increase in the use of the Net [v]. The increased use of social media has also significantly affected how research is spread. Circulated articles through social media are more visible than not circulated articles [6]. Various scientific studies take examined this relationship, and about have institute a positive correlation betwixt article citations and Twitter exposure [7–9].

Studies focusing on new media technologies in connexion with the digital historic period since the 2000s have taken an of import place in communication studies [ten]. In their all-encompassing studies on research topics in communication journals, Elisabeth Günther and Emese Domahidi (2017) observed that the Internet and social media have become the most important focus for communication research, in parallel with classical media, such as Television set or newspaper [10]. Social media is an of import discipline and practice in both interdisciplinary and communication fields [11–14]. Social media research is encouraged in the field of communication, as people today present themselves through digitally networked platforms. Therefore, this report aimed to demonstrate the upshot of social media on citation numbers of manufactures in communication-based journals. The human relationship between the traditional commendation numbers of articles and social media posts was analyzed in present study. Thus, it was aimed to shed light on the relationship between social media usage and the number of article citations in the field of communication.

Literature review

The emergence of social media took place simultaneously with Web 2.0. With the introduction of Web 2.0 into our lives, the Cyberspace has become individualized, and utilise of social networks increased gradually. The Internet has get an interactive virtual world from a read-only state, and it has brought a unlike dimension to communication [12]. Today, social media is a broad network of interactions where people from many areas [xv]. In detail, Internet has become a part of life due to the widespread use of smartphones. The majority of people actively use social media in daily life [sixteen]. A contempo study has stated that lxx% of peoples in the United states have at least one social media account nowadays. The peoples over 65 years old of 62% accept a social media account and they are regularly on social media. This observation is as well similar for adolescents. The using of social networks has been reported as 77% for teenagers anile 13–16 years in 25 European countries [16, 17]. These social network users interact for an average of more than two.4 hours a day on social media [18]. This increased instant interaction has further increased the employ of social media. Beside, social media platforms allows contained sharing, regardless of age, venue, and gender. Thus, information spreads rapidly across a wide area [15, 18]. Additionally, social media platforms ensure elementary interaction pathways between people, companies, and scientists without leaving the desk. Therefore, many scientists employ social media in their personal or professional person lives [19].

The virtually usually used platform for the purpose of spreading science is Twitter [20]. Twitter is the most pop microblogging platform present. This platform allows the publication of short messages by its users and enables them to communicate with each other. Evan Williams, Biz Rock, and Jack Dorsey created Twitter in March 2006 and brought into use in July 2006. Twitter has become one of the 10 most visited websites in 2013 and was divers every bit "the SMS of the Net" [21, 22]. In 2019, it was reported that in that location were 330 million monthly and 145 1000000 daily agile Twitter users. Present, it was reached 339 million users in 2020 [23]. The number of Twitter users has been increasing daily. Today, Twitter ranks as the world's second almost widely used social network. Twitter users can follow a chat and discuss a topic using messages named "tweets." Tweets are constrained to 140 characters of text. Subsequently, this limit was increased to 280 characters. Twitter allows the sharing of photos or videos [24]. Twitter was initially used to share news almost the lives of celebrities. Afterward, it reached a broader audience quickly, especially with the participation of famous names and the involvement of political campaigns. On average, approximately 98 thousand tweets are sent every minute on the platform, allowing an excellent interaction. Given the ascension in popularity of Twitter, its use is increasing in all parts of society [25]. This widespread use has also caught the attention of the scientific community. The use of Twitter as a tool for the dissemination of academic manufactures has soon become the focus of attention in the scientific world.

Academic output has increased gradually worldwide. Therefore, eliminating the relevant from the irrelevant has become essential for the scientific world. Thus, an touch on calibration has been necessitated the published articles [26]. The principal touch on of the published article has been measured past its citations [26]. All the same, article citations have recently become questionable due to negative factors, such every bit the wearisome procedure of identifying truly impactful articles. The long wait time required the emergence of the articles' importance has led to need for an culling metric scale [27].

Today, non-traditional metrics, altmetrics, are increasingly used to measure the real-time reach and influence of a scientific article [26, 28]. The term altmetrics was first proposed by Jason Priem in 2010 [29]. Thereafter, it has gained broad apply in highlighting previously unknown and unrecognized scholarly bear on metrics of studies [26, 30]. The alternative metric scores play a role in complementing traditional metrics or indicators [31]. Many publishers, such equally SAGE, Taylor-Francis Grouping, Elsevier, Nature Publishing Group, and Public Library of Science provide much information to their readers by their altmetrics evaluating system [32]. These altmetrics are calculated by various methods, including "Altmetric" and "Plum Analytics" [33]. All altmetrics that are an culling to the traditional citation system provide a score for the research output.

These scores have become bonny for researchers [34]. Many scientists believe that these alternative metric scores prove the real impact of published manufactures [35–37]. Many web-based platforms play a pregnant part in obtaining an altmetric score [11, 31]. With the data obtained from these platforms, a digital score was acquired for academic output [11]. All altmetrics are based on the using social media and other online tools for disseminating scholarly information [38]. The use of social media platforms contributes significantly the spread of shared data in a wider surround. Thus, the sharing of academic output on social media accounts tin can achieve more people faster by eliminating the waiting period in the traditional commendation organization [39, xl]. They take also allowed the touch on of articles to be more than immediately adamant, contrary to traditional citation metrics [41].

However, some concerns remain that the altmetric score tin can exist manipulated [42, 43]. In particular, the use of automatic bot can affect the altmetric scores of articles [44]. Farther, Twitter accounts tin impact the results of shared manufactures. These account holders may be social workers, companies, or politicians, and would have more than followers than others [45, 46]. Thus, some researchers suggest the use of "alt‑index" to measure the social visibility of scientific research [6]. Similarly, Haustein et al. argued that social media metrics could non actually be regarded every bit alternatives to traditional citations; hence, they proposed these metrics equally promoters of traditional citations [11]. The authors suggested the use of "Twitter Coupling" to deal with these concerns [38]. Although this may be a solution in that location is a consensus in many studies that social media usage will increase the impact of academic papers, thus ignoring these concerns [47, 48].

The potential of social media platforms to connect with other fields raises various scientific questions [49]. Therefore, the papers in the social sciences and humanities are more oft found on social media platforms [11]. Today, social interaction is and so intertwined with media that it is not possible to separate social media from the media sector. Thus, most studies related to social media take been published in the communication sciences. This increased usage of these social networks has led to the research question, "How are altmetrics and citation measures related in communication journals?" Tonia et al. (2016) stated that in that location were no statistical differences betwixt tweeted and non-tweeted papers regarding their citation numbers [50]. Costas et al. (2015) institute simply weak correlations in citations suggested past altmetrics and traditional citation analysis [35]. Further, some articles can be more attractive than other on social media platforms. Hence, some researchers take argued that in that location is a difference between social affect and existent impact [eleven]. Still, Thelwall et al. (2013) found that altmetrics was associated with citation counts [51]. Some other report stated that there is a positive human relationship betwixt social media posts and bookish citations [52]. Similarly, Shuai et al. (2012) detected significant correlations between tweets and early citations on iv,606 pre-prints articles [viii]. However, there is no consensus in the studies that to evaluate between tweeted and non-tweeted papers regarding their commendation numbers in communication scientific discipline, which is the scientific field mostly associated with social media and Twitter. The studies related to social media are encouraged in the field of communication as people present themselves through digitally networked platforms today. Therefore, it was hypothesized that there might be a correlation betwixt Twitter posts and traditional citations the manufactures in the tiptop x communication-based journals.

Materials and methods

Study blueprint

The present study was designed equally a retrospective cross-exclusive report. The aim was to examine the event of Twitter and other social media platforms on academic citations. Therefore, the pinnacle ten advice-based journals [9] were evaluated based on the SCImago Journal & Country Rank (cited in 2019). Information technology was used the SCImago Journal & Land Rank search field to select journals and filtered only "communication" journals. The choice criteria were the top ten communication-based journals according to their SCImago Periodical Rank indicator. This indicator is a measure of journals' academic bear upon and accounts for both the number of citations received by a journal and the importance or prestige of the journals in which the citations [53]. The bear upon factor of these journals was ≥ 2, and the quartile (Q) index was Q1. All x journals had similar indexes and like impact factors. It was assumed that this would reduce the potential for unwanted variation differences in social media activity.

Touch on Cistron: The affect factor has been defined as an indicator of academic periodical. Information technology reflects the year'southward average number of citations per newspaper published during the preceding two years. It is often used equally a relative indicator of a journal's importance in its field. The journals with loftier impact factors are thought to exist more important than those with low bear upon factors [54].

Q index: The journals' rank in each specific category is separated into quartiles past the Journal Citation Report and SCImago Journal and Country Rank: Q1, Q2, Q3 and Q4. Q1 comprises the top 25% of journals in the listing; Q2, Q3, and Q4 comprise 25% to 50%, fifty% to 75%, and 75% to 100% of journals in the listing, respectively (https://www.mondragon.edu/en/web/biblioteka/publications-impact-indexes).

These Journals "Political Communication (Q1, IF: iv.339)", "Journal of Advertising (Q1, IF: 6.302)", "Periodical of Advice (Q1, IF: 4.846)", Big Data and Society (Q1, IF: iv.577), Applied Linguistics (Q1, IF: 4.286), Advice Methods and Measures (Q1, IF: 5.281), New Media and Society (Q1, IF: 4.577), Man Communication Enquiry (Q1, IF: iii.540), Public Opinion Quarterly (Q1, IF: 2.494), and Digital Journalism (Q1, IF: 4.476) were included in this present written report (Table 1).

Information collection

All issues of these journals in 2018 were reviewed through the journals' web pages. All published articles in this year were evaluated on the web pages' archive. The appointment range was considered based on published bug in the journals. Simply original articles (meta-analyses, systematic reviews, original research articles, and research notes) in 2018 were included in this report. Manufactures such as editorials, book review articles, case reports, letters to the editor, and other non-research correspondences were excluded.

The findings of the articles (championship, doi number, commodity type) were recorded. In January 2021, the title of the article or doi number was searched one by one in Google Scholar (GS) and Web of Science (WoS) Clarivate. The traditional citation numbers (GS and WoS) of these articles were recorded. The tweet number and social media posts of these articles were searched by their metric evaluating arrangement (https://www.altmetric.com/) and recorded. The data were appraised almost three years after the articles' publication date. It was thought that this menstruum would allow the impact of published manufactures (the citations and Twitter mentions) to be fully observed.

Results

Seven hundred and eleven articles were published in the height ten communication-based journals in 2018. After the exclusion criteria were applied, 572 articles were included for analysis. A full of 570 articles (99.7%) were cited at to the lowest degree once on GS, and 518 articles (90.half-dozen%) were cited at to the lowest degree one time on WoS. The total cumulative number of citations for all the articles was 21,242 for GS and 5,874 for WoS. The number value of citations ranged from 0 to 868 on GS, and 0–235 on WoS. The median number of citations was 19 citations (interquartile range (IQR): 0–868 citations) for GS, and 5 citations (IQR: 0–235 citations) for WoS (Table 2).

In all, 522 articles (91.iii%) were posted at to the lowest degree one time on Twitter or other platforms. The total number of mentions on all social media platforms was l,624 items. Overall, the almost-used social media platform was Twitter. The bulk of articles (n: 500; 87.4%) were mentioned at least once on Twitter, and these articles had cumulatively tweets 13,438 tweet. The median value of Twitter posts was 9 tweets (IQR: 0–502 tweet).

The median citation value of articles on GS was 21 citations (IQR: 0–868) for the articles that had been tweeted at least one. However, it was nine (IQR: 0–72) citations for non-tweeted articles. Farther, the median WoS citation number was five (IQR: 0–235) for tweeted articles and two (IQR: 0–19) for not-tweeted manufactures.

The tweeted articles were cited more often than those with no tweets on both platforms (for GS: Isle of mann-Whitney U: 10107, Z: -6.022, p< 0.001; for WoS: Isle of mann-Whitney U: 10547, Z: -v.699, p< 0.001, respectively). This observation was likewise similar for the other platforms (for GS: Isle of mann-Whitney U: 6493, Z: -5.875, p< 0.001; for WoS: Mann-Whitney U: 6735.5, Z: -5.671, p< 0.001, respectively) (Tabular array 3).

It was observed that a significant correlation betwixt the number of Twitter posts and the number of citations in GS (r = 0.44, p<0.001) and in WoS (r = 0.fifty, P<0.001). Similarly, there was as well a positive correlation between the number of mentions on all platforms and the number of citations in GS (r = 0.83, p<0.001) and WoS (r = 0.71, p<0.001) (Fig ane).

Fig one. The correlation between citation of manufactures, and metric value and Twitter posts.

A. The relationship betwixt metric value of articles and Google scholar citations. B. The human relationship between metric value of articles and Web of Scientific discipline citations. C. The human relationship between Twitter posts of articles and Web of Scientific discipline citations. D. The relationship betwixt Twitter posts of articles and Google Scholar citations.

https://doi.org/10.1371/periodical.pone.0263725.g001

Discussion

Social networks in academia are apace improving, and significantly increasing use by the scientific customs [55]. Many journals ofttimes use these tools for advertising and sharing information [56]. Social media platforms accept brought another dimension to admission the information. With developments in social sharing platforms, in that location has been a transition to the digital historic period of accessing data [57]. Thus, these platforms accept presented new opportunities for researchers to extend their publications the scientific gild [36, 58]. Similarly, this present study establish that the articles exposed to social media were cited more than the articles not posted on social media. This study showed that the visibility of articles might be increased by sharing them on social media, which allows the real furnishings of the manufactures to emerge more chop-chop.

By and large, the use of all networks has a similar effect, only the most used platform for this purpose is Twitter. Twitter allows for the rapid sharing of information inside seconds of posting a tweet. Thus, the dissemination rate of tweets increases exponentially [59]. As in other studies, it was establish that more utilize of Twitter than other platforms in this study. Moreover, a positive correlation was observed betwixt the altmetric score, Twitter posts, and citation rate of articles. The articles that were tweeted at least once were cited more than those with no posts on both platforms (for GS, p <0.001; and for WoS, p <0.001). The findings back up the conclusion that Twitter activity may reflect the quality of articles or increment their citations. Thus, the measure of social platforms based on tweets should be used to complement the traditional metrics of article citations.

Especially the science of advice is the social sciences field most related to social networks. The traditional publishing continues in the communication sciences, but its adoption of social media-related studies is increasing daily [x, 14]. Therefore, sharing and disseminating the articles in advice journals may significantly increase their commendation rates. This present study revealed this human relationship and highlighted the impact of using social networks in the academic world. Thus, authors and journals should share all manufactures using social media tools to increase the affect of the article.

The use of social media platforms in the scientific earth will make an important contribution to traditional metric systems. Published articles tin be posted on social media to reach more people, disseminate data chop-chop and increase their bear on faster [60]. Further, academic journals' use of Twitter volition promote the journals and increase the citation numbers of the articles [9, 60]. Many journals share all of their articles published on their social media accounts. Some journals only share articles they deem important. All the same, increasing the visibility of articles on social media platforms could exist a tool for reaching more than people. Thus, this report shows that Twitter posts could mediate these manufactures to reach more than people.

The results of this report show that articles with exposure to social media had higher commendation rates. There was besides a positive correlation between exposure to social media and article citations. Therefore, the scientist and journals should develop new projects to increase the usage of social media.

All the same, the present written report has some limitations. First, it analyzed only the number of citations and the number of tweets and did not evaluate their content or the Twitter account holders. 2nd, this study evaluated only the top 10 journals in the communication science. 3rd, multiple factors (such every bit sending articles to the printing at the same time, focusing on some specific communication topics, and evaluating popular topics) may play a part in the emergence of the articles' impact. Posting articles on Twitter is only ane correspondent to this touch. Farther, this study examined the relationship between the number of Twitter posts and the number of citations of articles. However, the cause of the relationship was not analyzed. Therefore, more work is needed to explain potential causes of the relationships between posts and citations of an article. Nevertheless, this report presented significant findings that highlight the importance of using social media in academia.

References

1. i. Burgess J, Bruns A. Twitter archives and the challenges of" Big Social Data" for media and advice research. M/C Journal. 2012;15(5).
   • View Commodity
   • Google Scholar
2. 2. Obar JA, Wildman SS. Social media definition and the governance challenge-an introduction to the special issue. Telecommunication policy. 2015;39(9):745–750.
   • View Article
   • Google Scholar
3. 3. Ross C, Terras Chiliad, Warwick C, Welsh A. Enabled backchannel: Briefing Twitter use past digital humanists. Journal of Documentation. 2011;67(2): 214–237.
   • View Commodity
   • Google Scholar
4. four. Paradis North, Knoll MA, Shah C, Lambert C, Delouya Grand, Bahig H, et al. Twitter: A Platform for Broadcasting and Give-and-take of Scientific Papers in Radiations Oncology. American Journal of Clinical Oncology. 2020;43(6):442–445. pmid:32167936
   • View Article
   • PubMed/NCBI
   • Google Scholar
5. 5. Lenhart A, Purcell K, Smith A, Zickuhr Thou. Social Media & Mobile Cyberspace Use among Teens and Young Adults. Millennials. Pew internet American life project. 2010.
   • View Article
   • Google Scholar
6. half-dozen. Hassan S-U, Iqbal Southward, Aljohani NR, Alelyani S, Zuccala A. Introducing the 'alt-index'for measuring the social visibility of scientific enquiry. Scientometrics. 2020;123:1407–1419.
   • View Commodity
   • Google Scholar
7. seven. Eysenbach Chiliad. Tin can tweets predict citations? Metrics of social bear upon based on Twitter and correlation with traditional metrics of scientific impact. Journal of medical Net enquiry. 2011;xiii(4):e123. pmid:22173204
   • View Article
   • PubMed/NCBI
   • Google Scholar
8. 8. Shuai Ten, Pepe A, Bollen J. How the scientific customs reacts to newly submitted preprints: Article downloads, twitter mentions, and citations. PloS 1. 2012;vii(11):e47523. pmid:23133597
   • View Article
   • PubMed/NCBI
   • Google Scholar
9. ix. Peoples BK, Midway SR, Sackett D, Lynch A, Cooney Atomic number 82. Twitter predicts citation rates of ecological research. PLoS One. 2016;xi(11):e0166570. pmid:27835703
   • View Article
   • PubMed/NCBI
   • Google Scholar
10. ten. Günther E, Domahidi Eastward. What Communication Scholars Write Well-nigh: An Assay of lxxx Years of Research in Loftier-Touch Journals. International Journal of Communication. 2017;11:3051–3071.
    • View Article
    • Google Scholar
11. 11. Haustein Due south, Costas R, Larivière Five. Characterizing social media metrics of scholarly papers: The event of document properties and collaboration patterns. PloS one. 2015;10(three):e0120495. pmid:25780916
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
12. 12. Kazaz M, Özkent Y. The use of Twitter in synchronous with television series: A inquiry on students of advice kinesthesia. Selcuk Communication. 2016(9):205–24.
    • View Commodity
    • Google Scholar
13. 13. Evans JA, Foster JG. Metaknowledge. Science (New York, NY). 2011;331(6018):721–5. pmid:21311014
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
14. 14. Rogers JJB. The use of social media and its impact for enquiry. 2019;14(3):5022–4.
    • View Commodity
    • Google Scholar
15. 15. O'Leary S, Sheehan K, Lentz S. Small Business Smarts: Edifice Buzz with Social Media: Building Buzz with Social Media: ABC-CLIO; 2011.
    • View Article
    • Google Scholar
16. 16. Greenwood S, Perrin A, Duggan Grand. Social media update 2016. Pew Research Heart. 2016;xi(2):1–eighteen.
    • View Commodity
    • Google Scholar
17. 17. Hadjipanayis A, Efstathiou East, Altorjai P, Stiris T, Valiulis A, Koletzko B, et al. Social media and children: what is the paediatrician's role? European journal of pediatrics. 2019;178(ten):1605–12. pmid:31468108
    • View Article
    • PubMed/NCBI
    • Google Scholar
18. eighteen. Appel One thousand, Grewal Fifty, Hadi R, Stephen AT. The time to come of social media in marketing. Periodical of the Academy of Marketing Science. 2020;48(1):79–95. pmid:32431463
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
19. 19. Chandrasekar T, Goldberg H, Klaassen Z, Wallis CJD, Leong JY, Liem Southward, et al. Twitter and bookish Urology in the United States and Canada: a comprehensive cess of the Twitterverse in 2019. BJU Int. 2020;125(one):173–81. pmid:31602782
    • View Article
    • PubMed/NCBI
    • Google Scholar
20. xx. López-Goñi I, Sánchez-Angulo G. Social networks as a tool for science communication and public appointment: focus on Twitter. FEMS Microbiology Messages. 2017;365(2).
    • View Commodity
    • Google Scholar
21. 21. The summit 500 sites on the web [Available from: https://www.alexa.com/topsites.
22. 22. D'Monte L. Swine flu'south tweet tweet causes online flutter. Business Standard. 2009;29.
    • View Article
    • Google Scholar
23. 23. Twitter: number of monthly active users 2010–2019: Statista Enquiry Department; 2021 [Available from: https://www.statista.com/statistics/282087/number-of-monthly-active-twitter-users/.
24. 24. Webb S. Twitter employ in physics conferences. Scientometrics. 2016;108(3):1267–86. pmid:27570319
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
25. 25. Haustein Southward, Peters I, Sugimoto CR, Thelwall One thousand, Larivière V. Tweeting biomedicine: An analysis of tweets and citations in the biomedical literature. Journal of the Association for Data Science and Engineering. 2014;65(iv):656–69.
    • View Commodity
    • Google Scholar
26. 26. Warren Hr, Raison Northward, Dasgupta P. The Rise of Altmetrics. JAMA. 2017;317(2):131–ii. pmid:28097363
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
27. 27. Bornmann Fifty. Do altmetrics signal to the broader touch of enquiry? An overview of benefits and disadvantages of altmetrics. Journal of informetrics. 2014;viii(4):895–903.
    • View Article
    • Google Scholar
28. 28. Bornmann L, Haunschild R. Practise altmetrics correlate with the quality of papers? A large-calibration empirical study based on F1000Prime data. PloS one. 2018;thirteen(5):e0197133. pmid:29791468
    • View Article
    • PubMed/NCBI
    • Google Scholar
29. 29. Priem JJT, September. I like the term# articlelevelmetrics, just it fails to imply* diversity* of measures. Lately, I'm liking# altmetrics. 2010;28.
    • View Article
    • Google Scholar
30. 30. Priem J, Groth P, Taraborelli D. The altmetrics collection. PLoS One. 2012;seven(xi):e48753. pmid:23133655
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
31. 31. Kousha K, Thelwall M. Tin can Google Scholar and Mendeley assist to assess the scholarly impacts of dissertations? Journal of Informetrics. 2019;thirteen(2):467–84.
    • View Article
    • Google Scholar
32. 32. Erdt M, Nagarajan A, Sin S-CJ, Theng Y-50. Altmetrics: an analysis of the state-of-the-art in measuring enquiry impact on social media. Scientometrics. 2016;109(two):1117–66.
    • View Article
    • Google Scholar
33. 33. Liu J, Adie E. New perspectives on article-level metrics: developing ways to appraise research uptake and impact online. Insights. 2013;26(2):153–8.
    • View Article
    • Google Scholar
34. 34. Braun T, Glänzel W, Schubert A. A Hirsch-type alphabetize for journals. Scientometrics. 2006;69(1):169–73.
    • View Article
    • Google Scholar
35. 35. Costas R, Zahedi Z, Wouters P. Do "altmetrics" correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the Clan for Information Science Technology. 2015;66(10):2003–19.
    • View Commodity
    • Google Scholar
36. 36. Hassan South-U, Imran Thousand, Gillani U, Aljohani NR, Bowman TD, Didegah F. Measuring social media activity of scientific literature: an exhaustive comparing of scopus and novel altmetrics big information. Scientometrics. 2017;113(2):1037–57.
    • View Article
    • Google Scholar
37. 37. Repiso R, Castillo-Esparcia A, Torres-Salinas D. Altmetrics, alternative indicators for Web of Science Communication studies journals. Scientometrics. 2019;119(ii):941–58.
    • View Article
    • Google Scholar
38. 38. Hassan Southward-U, Aljohani NR, Shabbir M, Ali U, Iqbal S, Sarwar R, et al. Tweet Coupling: a social media methodology for clustering scientific publications. Scientometrics. 2020;124:973–91.
    • View Article
    • Google Scholar
39. 39. Ananiadou S, Thompson P, Nawaz R, editors. Enhancing search: Events and their discourse context. International conference on intelligent text processing and computational linguistics; 2013: Springer.
40. 40. Shu F, Lou W, Haustein S. Can Twitter increase the visibility of Chinese publications? Scientometrics. 2018;116(1):505–19.
    • View Commodity
    • Google Scholar
41. 41. Zahedi Z, Costas R. Full general discussion of data quality challenges in social media metrics: Extensive comparison of four major altmetric data aggregators. PLoS I. 2018;13(5):e0197326. pmid:29772003
    • View Article
    • PubMed/NCBI
    • Google Scholar
42. 42. Bartneck C, Kokkelmans S. Detecting h-alphabetize manipulation through self-citation assay. Scientometrics. 2011;87(1):85–98. pmid:21472020
    • View Article
    • PubMed/NCBI
    • Google Scholar
43. 43. Kwok R. Research impact: Altmetrics make their mark. Nature. 2013;500(7463):491–three. pmid:23977678
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
44. 44. Haustein Due south, Bowman TD, Holmberg 1000, Tsou A, Sugimoto CR, Larivière 5. Tweets as impact indicators: Examining the implications of automatic "bot" accounts on Twitter. Journal of the Association for Information Science Engineering science. 2016;67(1):232–8.
    • View Article
    • Google Scholar
45. 45. Quercia D, Kosinski M, Stillwell D, Crowcroft J, editors. Our twitter profiles, our selves: Predicting personality with twitter. 2011 IEEE third international briefing on privacy, security, risk and trust and 2011 IEEE 3rd international conference on social computing; 2011: IEEE.
46. 46. Tsou A, Bowman TD, Ghazinejad A, Sugimoto CR, editors. Who tweets near science? Issi; 2015: Istanbul.
47. 47. Ovadia S. Exploring the potential of Twitter as a enquiry tool. Behavioral and Social Sciences Librarian. 2009;28(4):202–5.
    • View Commodity
    • Google Scholar
48. 48. Darling ES, Shiffman D, Côté IM, Drew JA. The role of Twitter in the life cycle of a scientific publication. arXiv preprint arXiv:. 2013.
49. 49. Hermida A. Tell anybody: Why we share and why it matters: Anchor Canada; 2016.
    • View Article
    • Google Scholar
50. fifty. Tonia T, Van Oyen H, Berger A, Schindler C, Künzli Due north. If I tweet volition you cite? The effect of social media exposure of articles on downloads and citations. International journal of public health. 2016;61(4):513–xx. pmid:27193574
    • View Article
    • PubMed/NCBI
    • Google Scholar
51. 51. Thelwall M, Haustein S, Larivière Five, Sugimoto CR. Practise altmetrics work? Twitter and ten other social web services. PloS one. 2013;8(v):e64841. pmid:23724101
    • View Article
    • PubMed/NCBI
    • Google Scholar
52. 52. Zhang D, Earp BE. Correlation Between Social Media Posts and Bookish Citations of Orthopaedic Inquiry. J Am Acad Orthop Surg Glob Res Rev. 2020;4(9):e20.00151. pmid:32890011
    • View Article
    • PubMed/NCBI
    • Google Scholar
53. 53. Falagas ME, Kouranos VD, Arencibia-Jorge R, Karageorgopoulos DE. Comparison of SCImago journal rank indicator with journal impact factor. The FASEB journal. 2008;22(8):2623–8. pmid:18408168
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
54. 54. Garfield E. The history and meaning of the periodical touch cistron. jama. 2006;295(i):90–3. pmid:16391221
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
55. 55. Regenberg A. Science and Social Media. Stalk Cells Transl Med. 2019;8(12):1226–9. pmid:31282132
    • View Article
    • PubMed/NCBI
    • Google Scholar
56. 56. Kelly BS, Redmond CE, Nason GJ, Healy GM, Horgan NA, Heffernan EJ. The utilize of Twitter by radiology journals: an analysis of Twitter action and impact factor. Journal of the American Higher of Radiology. 2016;13(11):1391–6. pmid:27577594
    • View Article
    • PubMed/NCBI
    • Google Scholar
57. 57. Priem J, Hemminger BH. Scientometrics 2.0: New metrics of scholarly bear on on the social Web. Kickoff monday. 2010;15(seven).
    • View Commodity
    • Google Scholar
58. 58. Hassan S-U, Bowman TD, Shabbir Grand, Akhtar A, Imran M, Aljohani NR. Influential tweeters in relation to highly cited articles in altmetric big information. Scientometrics. 2019;119(1):481–93.
    • View Commodity
    • Google Scholar
59. 59. Nason GJ, O'Kelly F, Kelly ME, Phelan N, Manecksha RP, Lawrentschuk N, et al. The emerging utilise of T witter by urological journals. BJU international. 2015;115(3):486–90. pmid:24925047
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
60. threescore. Smith ZL, Chiang AL, Bowman D, Wallace MB. Longitudinal human relationship between social media activeness and article citations in the journal Gastrointestinal Endoscopy. Gastrointestinal endoscopy. 2019;90(1):77–83. pmid:30935934
    • View Article
    • PubMed/NCBI
    • Google Scholar

Share this post