What do academics ask their online networks? An ...

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11(1&2), 199-220. Figure 1: Percentage of questions per type. Academia.edu (present study) shown in pink; Twitter and Facebook users [1] shown in teal. 17. 14.
What do academics ask their online networks? An analysis of questions posed via Academia.edu Background

In the past decade, a number of online social networking sites (SNS) have been introduced. As a result of their popularity, several SNS aimed at the academic community have been launched. This poster focuses upon one affordance of academic SNS: the ability to pose questions to the wider community. This study set out to explore the types of questions academics pose to a specifically academic SNS, by analysing a sample of questions from the Academia.edu platform in terms of both topics and question types.

Katy Jordan Institute of Educational Technology, The Open University, UK [email protected]

Results

– question topics

Non-academic (33). Platform-specific comments (17)

Percentage

included questions about using the Academia.edu

site or statements of frustration with the service.

Personal information (5) is a small but distinct

category, in which academics’ posted information

such as their own name or email address. General

questions (11) were diverse and mainly rhetorical.

Data collection & analysis



Careers (14); for example: When data collection began (June 2014), Academia.edu included a total of 15,759 questions. A grounded theory

“I am interested in post doc in alternative approach was used in analyzing the content of the questions. The sample was constructed by random sampling;

fuel.I hv completed my phd on production of questions were added to the sample in batches of 50 until theoretical saturation had been achieved (a total of 300

biodiesel.pls guide me [sic]” questions, although 36 were excluded from coding). Questions were imported into nVivo for analysis. The coding

scheme was also applied to a random sample of 50 questions by a second coder. Cohen’s Kappa was calculated as a

measure of inter-coder reliability, which showed a high level of agreement (0.94).



Results – question types conceptual

The largest category, factual and

questions (71), comprised specialised questions

The results of the analysis in terms of the type of questions posed (using the

about subject-specialist topics and concepts. typology developed by Morris et al. [1]) is shown in Figure 1, with data from their

This included closed and open-ended questions. analysis based on generic SNS [1] as a comparison. A matrix coding query

For example:

showed that different types of questions are associated with different topics: “How common is natural deposition of ochre in

factual and conceptual questions are mainly factual (70%) or opinion (26%) caves in England and France?”

type; finding resources questions emphasise recommendations (75%); “What is effect of Kelo v City of New London US

promoting things mainly uses invitations (45%) or non-questions (36%), while

Supreme Court 2005 decision on use of eminent research focuses upon social connections (43%).

domain, in common law jurisdictions with

35

constitutional rights of property ownership?”

29

30

26

25

22

Finding resources (49) included requests to locate

specific resources (or even physical objects), and more 20

17 17

general requests for recommendations of resources

15 14 14

related to particular topics. For example:

“Does anyone have any general bibliography on

9

medieval pseudepigrapha? Thanks.”

10 7

6 5

5 4

3 2

1

0

0 Recommendation Opinion Factual Rhetorical Invitation Favor Social connection Offer Figure 2: The coding scheme of question topics which

knowledge

Figure 1: Percentage of questions per type. Academia.edu (present

study) shown in pink; Twitter and Facebook users [1] shown in teal.

References

[1] Morris, M.R., Teevan, J., and Panovich, K. 2010. What do people ask their social networks, and why? A survey study of status message Q&A behavior. In Proceedings of CHI 2010 (Atlanta, GA, USA, April 10-15, 2010), ACM, New York, NY, 1739-1748. [2] Papacharissi, Z. 2009. The virtual geographies of social networks: A comparative analysis of Facebook, LinkedIn and ASmallWorld. New Media Soc. 11(1&2), 199-220.

Conclusions

Academic-related categories which were distinct but less prevalent (raised by