-
Costas, R.; Rijcke, S. de; Marres, N.: "Heterogeneous couplings" : operationalizing network perspectives to study science-society interactions through social media metrics (2021)
0.01
0.0073257117 = product of:
0.10255996 = sum of:
0.10255996 = weight(_text_:media in 215) [ClassicSimilarity], result of:
0.10255996 = score(doc=215,freq=18.0), product of:
0.13212246 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.02820796 = queryNorm
0.7762493 = fieldWeight in 215, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=215)
0.071428575 = coord(1/14)
- Abstract
- Social media metrics have a genuine networked nature, reflecting the networking characteristics of the social media platform from where they are derived. This networked nature has been relatively less explored in the literature on altmetrics, although new network-level approaches are starting to appear. A general conceptualization of the role of social media networks in science communication, and particularly of social media as a specific type of interface between science and society, is still missing. The aim of this paper is to provide a conceptual framework for appraising interactions between science and society in multiple directions, in what we call heterogeneous couplings. Heterogeneous couplings are conceptualized as the co-occurrence of science and non-science objects, actors, and interactions in online media environments. This conceptualization provides a common framework to study the interactions between science and non-science actors as captured via online and social media platforms. The conceptualization of heterogeneous couplings opens wider opportunities for the development of network applications and analyses of the interactions between societal and scholarly entities in social media environments, paving the way toward more advanced forms of altmetrics, social (media) studies of science, and the conceptualization and operationalization of more advanced science-society studies.
-
Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020)
0.01
0.006248733 = product of:
0.04374113 = sum of:
0.034186658 = weight(_text_:media in 178) [ClassicSimilarity], result of:
0.034186658 = score(doc=178,freq=2.0), product of:
0.13212246 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.02820796 = queryNorm
0.25874978 = fieldWeight in 178, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=178)
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
0.019108946 = score(doc=178,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 178, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=178)
0.5 = coord(1/2)
0.14285715 = coord(2/14)
- Abstract
- Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.
- Date
- 20. 1.2015 18:30:22
-
Hellsten, I.; Leydesdorff, L.: Automated analysis of actor-topic networks on twitter : new approaches to the analysis of socio-semantic networks (2020)
0.00
0.0034533741 = product of:
0.048347235 = sum of:
0.048347235 = weight(_text_:media in 5610) [ClassicSimilarity], result of:
0.048347235 = score(doc=5610,freq=4.0), product of:
0.13212246 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.02820796 = queryNorm
0.36592746 = fieldWeight in 5610, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=5610)
0.071428575 = coord(1/14)
- Abstract
- Social media data provide increasing opportunities for the automated analysis of large sets of textual documents. So far, automated tools have been developed either to account for the social networks among participants in the debates, or to analyze the content of these debates. Less attention has been paid to mapping co-occurrences of actors (participants) and topics (content) in online debates that can be considered as socio-semantic networks. We propose a new, automated approach that uses the whole matrix of co-addressed topics and actors for understanding and visualizing online debates. We show the advantages of the new approach with the analysis of two data sets: first, a large set of English-language Twitter messages at the Rio?+?20 meeting, in June 2012 (72,077 tweets), and second, a smaller data set of Dutch-language Twitter messages on bird flu related to poultry farming in 2015-2017 (2,139 tweets). We discuss the theoretical, methodological, and substantive implications of our approach, also for the analysis of other social media data.
-
Radford, M.L.; Kitzie, V.; Mikitish, S.; Floegel, D.; Radford, G.P.; Connaway, L.S.: "People are reading your work," : scholarly identity and social networking sites (2020)
0.00
0.0024419043 = product of:
0.034186658 = sum of:
0.034186658 = weight(_text_:media in 5983) [ClassicSimilarity], result of:
0.034186658 = score(doc=5983,freq=2.0), product of:
0.13212246 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.02820796 = queryNorm
0.25874978 = fieldWeight in 5983, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=5983)
0.071428575 = coord(1/14)
- Abstract
- Scholarly identity refers to endeavors by scholars to promote their reputation, work and networks using online platforms such as ResearchGate, Academia.edu and Twitter. This exploratory research investigates benefits and drawbacks of scholarly identity efforts and avenues for potential library support. Design/methodology/approach Data from 30 semi-structured phone interviews with faculty, doctoral students and academic librarians were qualitatively analyzed using the constant comparisons method (Charmaz, 2014) and Goffman's (1959, 1967) theoretical concept of impression management. Findings Results reveal that use of online platforms enables academics to connect with others and disseminate their research. scholarly identity platforms have benefits, opportunities and offer possibilities for developing academic library support. They are also fraught with drawbacks/concerns, especially related to confusion, for-profit models and reputational risk. Research limitations/implications This exploratory study involves analysis of a small number of interviews (30) with self-selected social scientists from one discipline (communication) and librarians. It lacks gender, race/ethnicity and geographical diversity and focuses exclusively on individuals who use social networking sites for their scholarly identity practices. Social implications Results highlight benefits and risks of scholarly identity work and the potential for adopting practices that consider ethical dilemmas inherent in maintaining an online social media presence. They suggest continuing to develop library support that provides strategic guidance and information on legal responsibilities regarding copyright. Originality/value This research aims to understand the benefits and drawbacks of Scholarly Identity platforms and explore what support academic libraries might offer. It is among the first to investigate these topics comparing perspectives of faculty, doctoral students and librarians.
-
Manley, S.: Letters to the editor and the race for publication metrics (2022)
0.00
9.554473E-4 = product of:
0.013376262 = sum of:
0.013376262 = product of:
0.026752524 = sum of:
0.026752524 = weight(_text_:22 in 547) [ClassicSimilarity], result of:
0.026752524 = score(doc=547,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.2708308 = fieldWeight in 547, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=547)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 6. 4.2022 19:22:26
-
Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021)
0.00
8.1895484E-4 = product of:
0.011465367 = sum of:
0.011465367 = product of:
0.022930734 = sum of:
0.022930734 = weight(_text_:22 in 182) [ClassicSimilarity], result of:
0.022930734 = score(doc=182,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.23214069 = fieldWeight in 182, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=182)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 20. 1.2015 18:30:22
-
Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023)
0.00
8.1895484E-4 = product of:
0.011465367 = sum of:
0.011465367 = product of:
0.022930734 = sum of:
0.022930734 = weight(_text_:22 in 918) [ClassicSimilarity], result of:
0.022930734 = score(doc=918,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.23214069 = fieldWeight in 918, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=918)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 21. 3.2023 19:22:14
-
Wang, S.; Ma, Y.; Mao, J.; Bai, Y.; Liang, Z.; Li, G.: Quantifying scientific breakthroughs by a novel disruption indicator based on knowledge entities : On the rise of scrape-and-report scholarship in online reviews research (2023)
0.00
6.8246236E-4 = product of:
0.009554473 = sum of:
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 882) [ClassicSimilarity], result of:
0.019108946 = score(doc=882,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 882, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=882)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 22. 1.2023 18:37:33
-
Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023)
0.00
6.8246236E-4 = product of:
0.009554473 = sum of:
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 916) [ClassicSimilarity], result of:
0.019108946 = score(doc=916,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 916, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=916)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 21. 3.2023 19:22:02
-
Asubiaro, T.V.; Onaolapo, S.: ¬A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef (2023)
0.00
6.8246236E-4 = product of:
0.009554473 = sum of:
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 992) [ClassicSimilarity], result of:
0.019108946 = score(doc=992,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 992, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=992)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 22. 6.2023 14:09:06
-
Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023)
0.00
6.8246236E-4 = product of:
0.009554473 = sum of:
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 994) [ClassicSimilarity], result of:
0.019108946 = score(doc=994,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 994, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=994)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 22. 6.2023 18:07:12
-
Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023)
0.00
6.8246236E-4 = product of:
0.009554473 = sum of:
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 995) [ClassicSimilarity], result of:
0.019108946 = score(doc=995,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 995, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=995)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 22. 6.2023 18:11:50
-
Vakkari, P.; Järvelin, K.; Chang, Y.-W.: ¬The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995-2015 (2023)
0.00
6.8246236E-4 = product of:
0.009554473 = sum of:
0.009554473 = product of:
0.019108946 = sum of:
0.019108946 = weight(_text_:22 in 998) [ClassicSimilarity], result of:
0.019108946 = score(doc=998,freq=2.0), product of:
0.09877947 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02820796 = queryNorm
0.19345059 = fieldWeight in 998, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=998)
0.5 = coord(1/2)
0.071428575 = coord(1/14)
- Date
- 22. 6.2023 18:15:06
