Academics And Social Networking Sites: Benefits, Problems .
JOURNAL OF INTERACTIVEMEDIA IN EDUCATIONJordan, K and Weller, M 2018 Academics and Social Networking Sites: Benefits, Problemsand Tensions in Professional Engagement with Online Networking. Journal of InteractiveMedia in Education, 2018(1): 1, pp. 1–9, DOI: https://doi.org/10.5334/jime.448ARTICLEAcademics and Social Networking Sites: Benefits,Problems and Tensions in Professional Engagement withOnline NetworkingKaty Jordan and Martin WellerThe web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of onlinesocial networking by the academic community varies, and needs to be understood. This paper presents anindependent, novel analysis of a large-scale dataset published by Nature Publishing Group detailing theresults of a survey about academics use of online social networking services. An open coding approachwas used to analyse 480 previously unused text responses. The analysis revealed a wide range of benefitsand also problems associated with engaging with online networking, and tensions within this. The analysisprovides further insight into the nuances of uptake, by exploring clusters of co-reported benefits andproblems within the qualitative analysis. The findings will help move forward current debates surroundingsocial media use by academics from being viewed in solely beneficial terms, towards an understanding ofthe problems and tensions that arise through academic work online.Keywords: Digital scholarship; Academic networking; Social networking sites; Open educational practices;Networked participatory scholarshipIntroductionDigital scholarship is a research agenda concerned withhow the internet and digital technologies are transformingscholarly practice, encompassing a range of social andtechnological factors (Weller, 2011). Digital scholarshipcovers a range of academic activities. Some have gainedmore acceptance than others, for example online repositories of open access articles are part of common practice.Recognition of alternative forms of outputs such as blogshowever is still mixed. Digital scholarship has a numberof potential benefits for academics, Weller (2011) identifies these using Boyer’s framework across all four aspectsof scholarly activity: Discovery, Integration, Applicationand Teaching. Research has begun to emerge in examining how online networking is perceived by academicsthemselves, which is necessary to understand the contextwithin which these changes are taking place. Digital scholarship can take many forms, including the use of digitaltools, new methodologies, and approaches to pedagogy.This paper focuses on one aspect of digital scholarship,namely academic use of social networking sites (SNS). SNSare defined as online tools which allow users to create aprofile and make connections with others (boyd & Ellison,The Open University, GBCorresponding author: Katy Jordan(katy.jordan@gmail.com)2007; Hogan & Wellman, 2014). While SNS represent onlyone of a range of social media tools available to academics,they are of interest due to the development of a numberof services aimed specifically at academics (Nentwich &König, 2012), following the surge in popularity of generictools over the past decade (boyd & Ellison, 2007; Rainie &Wellman, 2012). This study is underpinned by a questionof whether academics’ use of such tools is creating newpatterns of academic networking or working more generally. This focus aligns the study with a stance derived fromdigital scholarship more generally, that is, of networkedparticipatory scholarship (Veletsianos, 2016; Veletsianos& Kimmons, 2013).Networked participatory scholarship is particularlyfocused upon the relationship between social, networkedtools and academic practice, through examining “scholars’participation in online social networks to share, reflectupon, critique, improve, validate, and otherwise developtheir scholarship” (Veletsianos & Kimmons, 2013, p.766).In her recent work focusing on academics’ use of Twitter,Stewart (2015) makes the link between networkedparticipatory scholarship and Boyer’s model of scholarship (Boyer, 1990). Through their use of the platform,the academics interviewed were found to enact Boyer’sdimensions of scholarship, but this model was insufficientas their practices go further, “fostering extensive cross-disciplinary, public ties and rewarding connection, collaboration, and curation between individuals rather than roles
Art. 1, page 2 of 9or institutions” (Stewart, 2015, p.318). This reframing ofbenefits to individuals harks back to Rainie and Wellman’s(2012) broader social notion of networked individualism. This study therefore locates itself in this conceptualspace, between digital scholarship, networked participatory scholarship, and traditional scholarship and aims toreveal more insights into how academics use social mediaand their attitudes towards it. Understanding the role ofonline networking within digital scholarly practice is challenging due to the variety of platforms available, the different purposes for which academics may use them, andchanges in the available technology and prevailing attitudes to their use over time.Several existing studies have addressed the extent ofuptake in terms of both the purposes for which academics use social media, and the specific platforms they use.Surveys typically employ Likert scale formats to assessacademics’ level of agreement with inventories of statements, derived from the potential ways in which socialmedia tools may enhance scholarly practice. However,these approaches assume that the inventories are complete and tend to be built upon pre-existing assumptionsthat the use of online networking is beneficial to academics (Jordan, 2016). The problems associated with the use ofsuch technologies by academics, and underlying patternsbetween the benefits and problems, are under-explored.Lupton (2014) is a notable exception, presenting a thematic analysis of text responses from an online survey ofacademics. Making connections and developing networks,openness and sharing, self-promotion, research, teaching,and support were identified as benefits (Lupton, 2014).Problems included privacy and the blurring of boundaries;lack of credibility; quality of content posted; time pressures; too much self-promotion by others; plagiarism, therisk of jeopardizing one’s career; social media use becoming an obligation, and becoming a target (Lupton, 2014).Lupton’s analysis presents a fuller, more balanced pictureof online academic networking, although it is a singleexample and may have limitations as a result of its sampling. The survey was mainly circulated via social media,and the sample includes a greater proportion of social scientists and early career researchers.In order to build a more complete inventory of bothbenefits and problems perceived by academics in relationto online networking, this paper presents an independent secondary analysis of a dataset based on a large scalesurvey of academics’ uses of online social networkingtools (Nature Publishing Group, 2014). While the headline findings (based on primarily quantitative data) havebeen reported (van Noorden, 2014), this analysis paysparticular attention to the qualitative responses andissues highlighted by academics in their own words. Thiscomplements and extends the work of Lupton (2014) inthat the demographic constituency of the Nature surveysample is contrasting, with a greater representation ofNatural Scientists and more senior academics. The Naturesurvey was circulated via publishers mailing lists ratherthan social media, so may have a better representation oflow use academics. The Nature dataset is also sufficientlylarge as to be able to look for underlying factors andJordan and Weller: Academics and Social Networking Sitesrelationships between benefits and problems of onlinenetworking for academics.Using the published Nature survey dataset as a basisfor novel analysis, the study therefore poses the followingresearch questions:i. What issues do academics choose to raise whenasked for free-text comments in relation to their useof SNS?ii. What connections exist between the issues raised ini), so whether groups of benefits or risks tend to beassociated?MethodsThis paper presents a secondary analysis of a surveydataset published online by Nature Publishing Group(Nature Publishing Group, 2014). The survey focusedupon academics’ use of social networking sites and wasactive from May to July 2014. Information about thesurvey was emailed to a total of 110,353 academics andacademic-related professionals through three publishers’mailing lists (Thomson Reuters ISI, Palgrave, and NaturePublishing Group). 3.2% of those invited respondedto the survey (3,579 responses). Responses from nonresearchers were excluded, leaving an overall sample sizeof 3,509 (ibid.). Although it is important to note that thesample demonstrates self-selection bias due to the opt-innature of the recruitment, the circulation of informationby email rather than social media itself may address theissue of over-representation of existing social media inother studies, and allows for inclusion of academics whoare lower level users of social media. The survey documentation notes that the responses received were in line withthe usage profile of nature.com (ibid.). Although most ofthe respondents were located in Europe (1,581) or NorthAmerica (1,062), the survey had a global reach, with 647respondents based in Asia, 95 in Australasia, 95 in SouthAmerica, and 29 in Africa. A range of job positions and subject areas were represented within the sample (Table 1).While a summary article of the survey results appearedin Nature as a News Feature in the same year (van Noorden,2014), the article was not comprehensive and the fulldataset was also published online via Figshare (NaturePublishing Group, 2014). The survey questions focusedupon uses and perceptions about social networking sitesand were mainly quantitative in nature. These includedsections about levels of familiarity with a range of socialnetworking sites (categorical); reasons for using social networking sites in general (Likert scale); and the ways whichacademics use a subset of specific sites (multiple checklist). The survey also included free-text responses, whichwere used as a source of illustrative quotes in the originalarticle but not fully analysed in themselves. As such, thedataset is an unusually large and diverse sample, and provides a useful source for further analyses.In order to gain an insight into the broader range ofissues related to use of social networking sites than thosecovered by the specific questions, the main focus of analysis here is upon the free text responses. A total of 861 academics chose to enter free text comments at the end of
Jordan and Weller: Academics and Social Networking Sitesthe survey, in response to the question ‘Please use the boxbelow to tell us about any other comments you may haveabout the social networking sites that you use’ (NaturePublishing Group, 2014).Responses were excluded from the analysis on thefollowing criteria: (i) blank or nonsense characters; (ii)yes/no answers; (iii) survey feedback; (iv) off-topic orambiguous responses; or (v) statements about use or nonuse of sites, if not supported with a reason (e.g. “I don’t useFacebook.”). This yielded a final sample of 480 responses,which were imported into nVivo for qualitative analysis.In analyzing the text responses, to elicit the issues forthe first research question, a content analysis approachwas used. An emergent coding scheme was developed inthe process of the analysis, rather than imposed, so as notto constrain the responses and allow the issues as perceived by academics to emerge (Strauss & Corbin, 1998).The first pass of coding categorized responses according towhether they were describing benefits and/or problemsassociated with using social networking sites, as the comments were typically polarized in this manner. Constantcomparison was used during the coding process, and axialcoding used to identify emergent themes.To address the second research question, whether theseissues were related, the coding data was exported fromnVivo in the form of matrix coding queries, which tabulated the frequency by which different codes co-occurredin academics’ free text statements. The frequency of cooccurrence was exported as a CSV file, and importedinto Excel, where the data was edited into a form (atwo-column spreadsheet, of pairs of linked codes) suitablefor import into a social network analysis program. This wasthen imported into Gephi (Bastian, Heymann & Jacomy,2009), to allow the co-occurrence of codes to be visualisedas a network. Presenting qualitative codes in this mannerprovides a novel way of viewing the relationships betweencodes, and allows clusters to be derived by applying analgorithm used to detect communities within social networks (Blondel, Guillaume, Lambiotte & Lefebvre, 2008).Table 1: Summary of demographic characteristics ofrespondents to the survey, and those who submittedtext responses.DemographicfactorsJob positionEntire survey(total n 3509)Free-text sample(total n herGraduate ercentageArts & HumanitiesSocial SciencesFormal SciencesNatural 184532761343.89.40.657.527.9Art. 1, page 3 of 9Responses were also coded according to categoriesrelating to job position and discipline (Table 1), to allowmatrix coding queries to be carried out in order to examinedifferences according to these factors. As this approach isquasi-statistical, formal tests were not applied due to thesubjectivity of coding.ResultsA striking asymmetry was present in the balance betweenacademics reporting benefits and problems associatedwith online networking. A greater proportion of academics (345; 72%) described problems rather than benefits(189; 39%; 11% having described both). The results ofthe analysis are summarised via the emergent codingscheme, which is shown for benefits and problems inTables 2 and 3 respectively. Note that the figures showthe number of academics whose responses contributed toeach category, and that a single academic’s response mayhave been coded in more than one category.Although a smaller proportion of the sample describedbenefits compared to problems, a range of benefits wereidentified from the text responses. The benefits weremore broadly distributed than the problems – that is, adominant benefit was not present.Table 2: Emergent coding scheme for benefits.BenefitsnBenefits for younger academicsDirectory of academicsDiscussionsDisseminationFind information and papersFind potential collaboratorsHelping othersImprove scientific processRaise own profileRecruitment and opportunitiesStay up-to-dateSupport multiple profilesTrack impact1316212617221261916231315Percentage (of ble 3: Emergent coding scheme for problems.ProblemsConcerns about commercialismDigital inclusion issuesDigital literacy issuesForbidden by institutionNot perceived to be usefulPrefer other networkingPrivacy and security concernsSocial aversionSpamTime concernsToo many sitesUnreliable information onlinen8729670393654191062825Percentage (of 345)2.32.08.41.720.311.310.415.75.530.78.17.2
Art. 1, page 4 of 9Beavers et al: Book ReviewsDissemination of research findings was the largest single category. This included dissemination in the traditionalsense, to other academics, but also through and openingup conversations about their work with other audiencesand making information available in different formats tothe traditional scientific paper. A corollary of dissemination via SNS is the ability to track the impact of work.Other related benefits included recruitment, in termsof finding potential candidates, and finding out aboutemployment opportunities.Dissemination: “I have started using Facebook andTwitter to communicate our research findings tolay people, other researchers, respectively.”Finding information and papers, and SNS as a mechanismof staying up-to-date, contrast with the problems of timeand information overload.Discussions: “They have been useful for following“meta” issues regarding research. Such as replicability, pre-registration, open access, etc. Thesediscussions are few and far between “in person”.Social networks, such as blogs and Twitter, providea wide range of opinions on such issues that maybe accessed at any time.”Find information and papers: “obtain new information on my subject easily and early”, “request papersthat I can not get on the network at my university.”Track impact: “Social networking sites give you aninstant feedback, which may be positive or negative but gives you an idea regarding the impact ofyour research.”The utility of being searchable (‘Googleability’ as one participant put it) is reflected in terms of the role of SNS as avirtual address book, finding potential collaborators, andraising your own profile.Raise own profile: “I find it is very important to havea presence online – not everyone can and shouldhave a blog or Twitter account – but it is importantto be able to be ‘searchable’ and ‘findable’.”Find potential collaborators: “Researchgate is great.You can artificially amplify your RG score by justadding comments to any old QandA. But I like thesite. It is easy to use, and as I said can lead to somenew international collaborations. This is particularly useful, as often at a national level there is acompetitiveness that can prevent collaboration.”Directory of academics: “keep in contact with professional colleagues, especially when they moveinstitutions.”This was perceived to be particularly beneficial foryounger academics, along with being able to draw upona wider network for help with particular methodologicalproblems.Benefits for younger academics: “I try to maintaina low profile because I am already deluged withrequests for help from doctoral students andresearchers who find me by email. Increasingone’s visibility (and your survey seems to assumeit) may be useful for new researchers but not foreveryone.”Recruitment and opportunities: “I find it a usefulway to reach other professionals whom I couldinterview for specific research projects.”Stay up-to-date: “Invaluable for keeping up socialconnections with research colleagues with whom Iwould otherwise have no personal contact.”, “I havefound both [Facebook and Twitter] surprisinglyuseful, perhaps mostly Twitter: I know am muchmore up to date on controversies as well as excitingnew stories.”In contrast to concerns about mixing the personal andprofessional, the facility to host multiple profiles andinteract with different audiences this way was highlightedby some as a benefit.Support multiple profiles: “I keep two accounts, aninformal real life account in which I talk about myprofession because it is part of my life, but it isdefinitely NOT a professional account, and a pseudonymous account. The latter is generally whereI post.”A small but interesting group of responses relate to thewider societal benefits of SNS, through their potentialto improve the efficiency of the scientific process, andaltruism.Helping others: “Social network is very useful toshare our expertise, knowledge to others whilelearning from them too.”Improve scientific process: “All research shouldbe open access. Researchers get too hung up onauthorship and publishers keep their informationtoo private, preventing other researchers frombenefiting from a peer’s data. The scientific community needs a platform which promotes a noncompetitive atmosphere and that is easy and effective to use. Basically. research benefits society onlyif shit gets done, so let’s get it done quicker and asa community.”The princ
social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a large-scale dataset published by Nature Publishing Group detailing the results of a survey about academics use of online social networking services. An open coding approach
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