Timothy D. Bowman

Big data, bigger dilemmas: A critical review

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain‐specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention—autonomy, opacity, generativity, disparity, and futurity—leading to questions and ideas for moving beyond dilemmas.

Tweets as impact indicators: Examining the implications of automated bot accounts on Twitter

This brief communication presents preliminary findings on automated Twitter accounts distributing links to scientific articles deposited on the preprint repository arXiv. It discusses the implication of the presence of such bots from the perspective of social media metrics (altmetrics), where mentions of scholarly documents on Twitter have been suggested as a means of measuring impact that is both broader and timelier than citations. Our results show that automated Twitter accounts create a considerable amount of tweets to scientific articles and that they behave differently than common social bots, which has critical implications for the use of raw tweet counts in research evaluation and assessment. We discuss some definitions of Twitter cyborgs and bots in scholarly communication and propose distinguishing between different levels of engagement—that is, differentiating between tweeting only bibliographic information to discussing or commenting on the content of a scientific work.

Transverse Patterning Reveals a Dissociation of Simple and Configural Association Learning Abilities in Rats with 192 IgG-Saporin Lesions of the Nucleus Basalis Magnocellularis

This experiment tests the hypothesis that the cholinergic nucleus basalis magnocellularis (NBM) is necessary for complex or configural association learning, but not elemental or simple association learning. Male Long-Evans rats with bilateral 192 IgG-saporin lesions of the NBM (n = 12) and sham-operated controls (n = 8) were tested in the transverse patterning problem, which provides a test of both simple and configural association learning. Rats were trained in phases to concurrently solve first one, then two, and finally three different visual discriminations; Problem 1 (A+ vs B- sign) and Problem 2 (B+ vs C-) could be solved using simple associations, whereas solving Problem 3 (C+ vs A-) required the ability to form configural associations. Consistent with our hypothesis, the NBM lesion group solved the simple discriminations in Problems 1 and 2 but showed impaired configural association learning in Problem 3. Additionally, when Problem 2 was introduced, previously high levels of performance on Problem 1 suffered more in the NBM lesion group than in the control group; this finding suggests an impairment in the ability of animals with NBM lesions to divide attention among multiple stimuli or to shift between strategies for solving different problems. Results support our argument that the NBM is critically involved in the acquisition of associative problems requiring a configural solution but not in problems that can be solved using only simple associations. The observed impairments in configural association learning and the apparent loss of cognitive flexibility or capacity are interpreted as reflecting specific attentional impairments resulting from NBM damage.

Astrophysicists on Twitter: An in-depth analysis of tweeting and scientific publication behavior

Purpose – The purpose of this paper is to analyze the tweeting behavior of 37 astrophysicists on Twitter and compares their tweeting behavior with their publication behavior and citation impact to show whether they tweet research-related topics or not. Design/methodology/approach – Astrophysicists on Twitter are selected to compare their tweets with their publications from Web of Science. Different user groups are identified based on tweeting and publication frequency. Findings – A moderate negative correlation (ρ=−0.339) is found between the number of publications and tweets per day, while retweet and citation rates do not correlate. The similarity between tweets and abstracts is very low (cos=0.081). User groups show different tweeting behavior such as retweeting and including hashtags, usernames and URLs. Research limitations/implications – The study is limited in terms of the small set of astrophysicists. Results are not necessarily representative of the entire astrophysicist community on Twitter and ...

Astrophysicists’ conversational connections on Twitter

Because Twitter and other social media are increasingly used for analyses based on altmetrics, this research sought to understand what contexts, affordance use, and social activities influence the tweeting behavior of astrophysicists. Thus, the presented study has been guided by three research questions that consider the influence of astrophysicists’ activities (i.e., publishing and tweeting frequency) and of their tweet construction and affordance use (i.e. use of hashtags, language, and emotions) on the conversational connections they have on Twitter. We found that astrophysicists communicate with a variety of user types (e.g. colleagues, science communicators, other researchers, and educators) and that in the ego networks of the astrophysicists clear groups consisting of users with different professional roles can be distinguished. Interestingly, the analysis of noun phrases and hashtags showed that when the astrophysicists address the different groups of very different professional composition they use very similar terminology, but that they do not talk to each other (i.e. mentioning other user names in tweets). The results also showed that in those areas of the ego networks that tweeted more the sentiment of the tweets tended to be closer to neutral, connecting frequent tweeting with information sharing activities rather than conversations or expressing opinions.

Differences in personal and professional tweets of scholars

Purpose – The purpose of this paper is to show that there were differences in the use of Twitter by professors at AAU schools. Affordance use differed between the personal and professional tweets of professors as categorized by turkers. Framing behaviors were described that could impact the interpretation of tweets by audience members. Design/methodology/approach – A three phase research design was used that included surveys of professors, categorization of tweets by workers in Amazon’s Mechanical Turk, and categorization of tweets by active professors on Twitter. Findings – There were significant differences found between professors that reported having a Twitter account, significant differences found between types of Twitter accounts (personal, professional, or both), and significant differences in the affordances used in personal and professional tweets. Framing behaviors were described that may assist altmetric researchers in distinguishing between personal and professional tweets. Research limitation...

Post-interdisciplinary frames of reference: exploring permeability and perceptions of disciplinarity in the social sciences

The ProQuest Dissertations and Theses database contains records for approximately 2.3 million dissertations conferred at 1,490 research institutions across 66 countries. Despite the scope of the Dissertations and Theses database, no study has explicitly sought to validate the accuracy of the ProQuest SCs. This research examines the degree to which ProQuest SCs serve as proxies for disciplinarity, the relevance of doctoral work to doctoral graduates’ current work, and the permeability of disciplines from the perspective of the mismatch between SCs and disciplinarity. To examine these issues we conducted a survey of 2009–2010 doctoral graduates, cluster-sampled from Economics, Political Science, and Sociology ProQuest SCs. The results from the survey question the utility of traditional disciplinary labels and suggest that scholars may occupy a post-interdisciplinary space in which they move freely across disciplinary boundaries and identify with topics instead of disciplines.

On the differences between citations and altmetrics: An investigation of factors driving altmetrics versus citations for finnish articles

This study examines a range of factors associated with future citation and altmetric counts to a paper. The factors include journal impact factor, individual collaboration, international collaboration, institution prestige, country prestige, research funding, abstract readability, abstract length, title length, number of cited references, field size, and field type and will be modeled in association with citation counts, Mendeley readers, Twitter posts, Facebook posts, blog posts, and news posts. The results demonstrate that eight factors are important for increased citation counts, seven different factors are important for increased Mendeley readers, eight factors are important for increased Twitter posts, three factors are important for increased Facebook posts, six factors are important for increased blog posts, and five factors are important for increased news posts. Journal impact factor and international collaboration are the two factors that significantly associate with increased citation counts and with all altmetric scores. Moreover, it seems that the factors driving Mendeley readership are similar to those driving citation counts. However, the altmetric events differ from each other in terms of a small number of factors; for instance, institution prestige and country prestige associate with increased Mendeley readers and blog and news posts, but it is an insignificant factor for Twitter and Facebook posts. The findings contribute to the continued development of theoretical models and methodological developments associated with capturing, interpreting, and understanding altmetric events.

Authorship, patents, citations, acknowledgments, tweets, reader counts and the multifaceted reward system of science

Building upon well‐established paradigms brought forth by such theorists as Robert K. Merton, Pierre Bourdieu, and Blaise Cronin, the panel will span the full cycle of academic production to show, through various bibliometric measures and other quantitative and qualitative analyses, how the reward system of science is evolving. While there is strong evidence to suggest that such forms of dissemination as social media output and blogging are being incorporated into scientific practices, scientific impact still remains principally assessed using measures such as authorship and citations, whilst other elements, such as acknowledgements, have received varying levels of regard at various times. Disciplinary considerations also arise. Using a wide range of approaches, measures, and datasets, the panelists will establish links between their individual research to create an empirically driven picture of the reward system of science and its indicators. Through the use of the Polldaddy application, audience members will answer questions and create an overview of their perception of the reward system of science.

Increasing our understanding of altmetrics: identifying factors that are driving both citation and altmetric counts

This study examines a range of factors associating with eventual citation and altmetric counts to a paper. The factors include research collaboration, institution impact, journal impact, journal open accessibility, and field type that will be modelled in association with citation counts, Twitter posts, Facebook posts and Mendeley readers. The results show that the factors driving increased citations are different from those driving increased altmetric events. The altmetric events differ from each other in terms of a few factors. The findings from this study can contribute to the continued development of theoretical models and methodological developments associated with capturing, interpreting, and understanding altmetric events. This work can also aid research policy makers with identifying important factors driving altmetric events.