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 limitations/implications – The study is limited by the sample population, survey instrument, low survey response rate, and low Cohen’s κ. Practical implications – An overview of various affordances found in Twitter is provided and a novel use of Amazon’s Mechanical Turk for the categorization of tweets is described that can be applied to future altmetric studies. Originality/value – This work utilizes a socio-technical framework integrating social and psychological theories to interpret results from the tweeting behavior of professors and the interpretation of tweets by workers in Amazon’s Mechanical Turk

A Systematic Identification and Analysis of Scientists on Twitter

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

Reactions of Generation Y to Luxury Hotel Twitter Promotions

Social media refers to the means of interactions among people in which they create, share, and exchange information and ideas in virtual communities and networks (Merriam-Webster, 2013). Social media marketing refers to the process of gaining website traffic or attention through social media sites (Evans, 2008). In today’s society, social media refers mainly to websites including (but not limited to) Facebook, Twitter, LinkedIn, and Google+. The most popular and fastest growing of these social media venues is Twitter. Twitter was founded in 2006 by Jack Dorsey, Evan Williams, and Biz Stone. Since 2006, almost 200 million users across the globe have joined the site; over 140 million tweets are “tweeted” daily (Picard, 2011). Twitter took advantage of a niche in the market, allowing 140 characters to express an idea or emotion. Twitter has changed the media world as a news source, tweeting real-time information from stories that arise (Picard, 2011). In the lodging industry, methods of social media to promote hotels are becoming more popular. Twitter, in particular, has emerged as a “moment of truth” for a hotel, demonstrating how instantly and tactfully hotels react to the thoughts and opinions of former, current, and potential guests. Studies have also suggested that “online social life mirrors offline relationships in many ways” (Moore, p. 440). Therefore, Twitter accounts should be viewed as an extension of the hospitality business, in particular lodging, echoing the relationship a customer would feel upon arrival to the hotel. Hotel marketing teams have reached “great success by driving demand to hotels through increased online advertising and web optimization” (Chipkin, 2013). This has increased overall customer views of the hotel without affecting the rate strategy of the property or brand. Twitter presence could, potentially, help a patron decide between two hotels, “If a promotion, experience or package is unique, it definitely works to generate bookings and helps put you first in a consumer’s mind when they are choosing between two or three hotels,” says Rachel Harrison of Hyatt Andaz (Chipkin, 2013). Hotel companies worldwide are investing in their social media networks. Certain hotels (i.e. W Barcelona) are even hiring social media and marketing managers whose responsibilities include instant Twitter feedback (Appendix 1). The purpose behind this investment is to maximize these social media accounts, creating feedback from all potential guests, allowing them to react to both positive and negative word of mouth. Social media managers have recently encountered an opportunity; Generation Y is becoming a target demographic. As Generation Y enters the workforce and begins a career, the exposure to hotel brands and types will increase. Luxury hotel stays are becoming more financially reachable to these Generation Y guests because of their career advancements (Fields, 2013). This study will serve to evaluate the added benefits from the adoption of social media channels, particularly Twitter

To follow or not to follow? How Belgian health journalists use Twitter to monitor potential sources

Digital technology, the internet and mobile media are transforming the journalism and media landscape by influencing the news gathering and sourcing process. The empowering capacities of social media applications may constitute a key element for more balanced news access and “inclusive journalism”. We will build on two contrasting views that dominate the social media sourcing debate. On the one hand, literature shows that journalists of legacy media make use of social media sources to diversify their sourcing network including bottom-up sources such as ordinary citizens. On the other hand, various authors conclude that journalists stick with their old sourcing routines and continue to privilege top-down elite sources such as experts and government officials. In order to contribute to this academic debate we want to clarify the Twitter practices of professional Belgian health journalists in terms of how they use the platform to monitor potential sources. Therefore, we examined the 1146 Twitter “followings” of six Belgian health journalists by means of digital methods and social network analysis. Results show that top-down actors are overrepresented in the “following” networks and that Twitter’s “following” function is not used to reach out to bottom-up actors. In the overall network, we found that the health journalists mainly use Twitter as a “press club” (Rupar, 2015) to monitor media actors. If we zoom in specifically on the “following” network of the health-related actors, we found that media actors are still important, but experts become the most followed group. Our findings also underwrite the “power law” or “long tail” distribution of social network sites as very few actors take a central position in the “following” lists while the large majority of actors are not systematically monitored by the journalists

Academic information on Twitter: A user survey

Although counts of tweets citing academic papers are used as an informal indicator of interest, little is known about who tweets academic papers and who uses Twitter to find scholarly information. Without knowing this, it is difficult to draw useful conclusions from a publication being frequently tweeted. This study surveyed 1,912 users that have tweeted journal articles to ask about their scholarly-related Twitter uses. Almost half of the respondents (45%) did not work in academia, despite the sample probably being biased towards academics. Twitter was used most by people with a social science or humanities background. People tend to leverage social ties on Twitter to find information rather than searching for relevant tweets. Twitter is used in academia to acquire and share real-time information and to develop connections with others. Motivations for using Twitter vary by discipline, occupation, and employment sector, but not much by gender. These factors also influence the sharing of different types of academic information. This study provides evidence that Twitter plays a significant role in the discovery of scholarly information and cross-disciplinary knowledge spreading. Most importantly, the large numbers of non-academic users support the claims of those using tweet counts as evidence for the non-academic impacts of scholarly researc

Tweeting Library and Information Science: a socio-topical distance analysis

The aim of this paper is to demonstrate how topical distance and social distance can provide meaningful results when analysing scholars’ tweets linking to scholarly publications. To do so, we analyse the social and topical distance between tweeted information science papers and their academic tweeters. This allows us to characterize the tweets of scientific papers, the tweeting behavior of scholars, and the relationship between tweets and citations