Authors : Matthew L Williams, Pete Burnap, Luke Sloan
New and emerging forms of data, including posts harvested from social media sites such as Twitter, have become part of the sociologist’s data diet. In particular, some researchers see an advantage in the perceived ‘public’ nature of Twitter posts, representing them in publications without seeking informed consent.
While such practice may not be at odds with Twitter’s terms of service, we argue there is a need to interpret these through the lens of social science research methods that imply a more reflexive ethical approach than provided in ‘legal’ accounts of the permissible use of these data in research publications.
To challenge some existing practice in Twitter-based research, this article brings to the fore: (1) views of Twitter users through analysis of online survey data; (2) the effect of context collapse and online disinhibition on the behaviours of users; and (3) the publication of identifiable sensitive classifications derived from algorithms.
URL : Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users’ Views, Online Context and Algorithmic Estimation
DOI : http://dx.doi.org/10.1177%2F0038038517708140
Authors : Qing Ke, Yong-Yeol Ahn, Cassidy R. Sugimoto
Metrics derived from Twitter and other social media—often referred to as altmetrics—are increasingly used to estimate the broader social impacts of scholarship. Such efforts, however, may produce highly misleading results, as the entities that participate in conversations about science on these platforms are largely unknown.
For instance, if altmetric activities are generated mainly by scientists, does it really capture broader social impacts of science? Here we present a systematic approach to identifying and analyzing scientists on Twitter.
Our method can identify scientists across many disciplines, without relying on external bibliographic data, and be easily adapted to identify other stakeholder groups in science.
We investigate the demographics, sharing behaviors, and interconnectivity of the identified scientists.
We find that Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists; under-representation of mathematical, physical, and life scientists; and a better representation of women compared to scholarly publishing.
Analysis of the sharing of URLs reveals a distinct imprint of scholarly sites, yet only a small fraction of shared URLs are science-related. We find an assortative mixing with respect to disciplines in the networks between scientists, suggesting the maintenance of disciplinary walls in social media.
Our work contributes to the literature both methodologically and conceptually—we provide new methods for disambiguating and identifying particular actors on social media and describing the behaviors of scientists, thus providing foundational information for the construction and use of indicators on the basis of social media metrics.
URL : A systematic identification and analysis of scientists on Twitter
DOI : https://doi.org/10.1371/journal.pone.0175368
Authors : Anabel Quan-Haase, Kim Martin, Lori McCay-Peet
Big Data research is currently split on whether and to what extent Twitter can be characterized as an informational or social network. We contribute to this line of inquiry through an investigation of digital humanities (DH) scholars’ uses and gratifications of Twitter.
We conducted a thematic analysis of 25 semi-structured interview transcripts to learn about these scholars’ professional use of Twitter.
Our findings show that Twitter is considered a critical tool for informal communication within DH invisible colleges, functioning at varying levels as both an information network (learning to ‘Twitter’ and maintaining awareness) and a social network (imagining audiences and engaging other digital humanists).
We find that Twitter follow relationships reflect common academic interests and are closely tied to scholars’ pre-existing social ties and conference or event co-attendance. The concept of the invisible college continues to be relevant but requires revisiting.
The invisible college formed on Twitter is messy, consisting of overlapping social contexts (professional, personal and public), scholars with different habits of engagement, and both formal and informal ties.
Our research illustrates the value of using multiple methods to explore the complex questions arising from Big Data studies and points toward future research that could implement Big Data techniques on a small scale, focusing on subtopics or emerging fields, to expose the nature of scholars’ invisible colleges made visible on Twitter.
URL : http://ir.lib.uwo.ca/fimspub/71/
Author : R
An experiment run in 2009 could not assess whether making monographs available in open access enhanced scholarly impact. This paper revisits the experiment, drawing on additional citation data and tweets. It attempts to answer the following research question: does open access have a positive influence on the number of citations and tweets a monograph receives, taking into account the influence of scholarly field and language?
The correlation between monograph citations and tweets is also investigated. The number of citations and tweets measured in 2014 reveal a slight open access advantage, but the influence of language or subject should also be taken into account. However, Twitter usage and citation behaviour hardly overlap.
URL : Revisiting an open access monograph experiment
Alternative location : https://rd.springer.com/article/10.1007/s11192-016-2160-6
Authors : Edward P. Randviir, Samuel M. Illingworth, Matthew J. Baker, Matthew Cude, Craig E. Banks
The Royal Society of Chemistry held, to our knowledge, the world’s first Twitter conference at 9am on February 5 th, 2015. The conference was a Twitter-only conference, allowing researchers to upload academic posters as tweets, replacing a physical meeting.
This paper reports the details of the event and discusses the outcomes, such as the potential for the use of social media to enhance scientific communication at conferences. In particular, the present work argues that social media outlets such as Twitter broaden audiences, speed up communication, and force clearer and more concise descriptions of a researcher’s work.
The benefits of poster presentations are also discussed in terms of potential knowledge exchange and networking.
This paper serves as a proof-of-concept approach for improving both the public opinion of the poster, and the enhancement of the poster through an innovative online format that some may feel more comfortable with, compared to face-to-face communication.
URL : Twittering About Research: A Case Study of the World’s First Twitter Poster Competition
Alternative location : http://f1000research.com/articles/4-798/v3
The aim of the paper is to identify the motive behind the social media indicators in focus to tweets and attempts to identify what is measured or indicated by tweets, based on these motives.
Documents with non zero tweets were manually collected from a source of 5 journals – Nature Biotechnology, Nature Nanotechnology, Nature Physics, Nature Chemistry and Nature Communications for the period January 2014 – October 2014 so as to depict the contemporary trend, as tweets tends to have L shaped curve in time-wise distribution.
Investigations suggest that the motives behind the tweets are research reach, research acceptance and research usage. Further analysis revealed that the motive behind self – tweets are research visibility, which is one of the attributes of social media and therefore self tweets may not be a complex problem as expected seeing that documents are self tweeted not more than once in most cases.
Furthermore, identifying and classifying tweets based on users – Publishers, Frequent tweeters who apparently tweet all documents of an issue and Authors will increase the effectiveness of altmetrics in research evaluation. It was also found that association between subjects can be identified by the analysis of tweets pattern among subjects.
Study proposes an overall hierarchical structure of impact based on the change/advancement instigated. The study confirms that tweets do measure non – academic intellectual impact that is not captured by traditional metrics.
URL : http://www.itlit.net/v2n2art2.pdf