Information-Centred Research - A Big Data Theory for Information Scientists

Information-centred research (ICR) is an information science e-research methodology that focuses on new information sources and particularly big data research for the social sciences and humanities. The ICR approach is an attempt to efficiently exploit new information sources for social science and humanities research purposes. ICR is a big data theory in the sense that it is for new information sources that are typically much larger than those analysed before for similar research issues, even if the data are not large enough to be computationally challenging.

The traditional problem-centred research (PCR) approach: starts with a domain-specific problem and then investigates a new information source to see whether it addresses the problem.
- e.g., New information source= hyperlinks; examples of domain-specific problems: Can hyperlinks be used like citations to evaluate scientific research? (domain=information science); Can hyperlinks be used like citations to track flows of international collaboration? (domain=information science); Can hyperlinks be used to track online political debates? (domain = communication science/politics)
The ICR approach: Starts with the new information source and then identifies research problems from a variety of domians that it may be relevant to.
- e.g., New information source= hyperlinks; examples of ICR approaches: What social science research problems are hyperlinks relevant to? (very general problem - ICR is typically more constrained than this in practice); What are hyperlinks used for in academic web spaces and which research problems or uses are relevant to them? (more specific problem).

Although the ICR task is to direct new information souces to relevant fields and problems, an ICR research approach can also involve developing methods to effectively extract useful information from the new data source(e.g., the Alternative Document Model counting methods used in link analysis). ICR researchers can work in five different ways.

ICR1 Identify relevant problems for a new information source and then attempt to solve them alone, for example leading to the publication of a solo conference paper or journal article.
ICR2 Identify relevant problems or a new information source and then attempt to solve them in conjunction with domain-specialist researchers, for example leading to the publication of a co-authored conference paper or journal article.
ICR3 Identify relevant problems for a new information source and then attempt to deliver them to domain-specialist researchers to solve, for example leading to the publication of a sole conference paper or journal article by the domain-specific researcher.
ICR4 Develop methods and descriptive analysis or initial theories to aid domain specialists to decide whether a new information source is relevant to them, and to help them exploit it. The results could typically be published in a sole-authored journal article, conference paper or magazine article. Note that ICR4 is similar to descriptive research, which is often used in the initial stages of programmes of research, and also similar to purely methodological research.
ICR5 Develop methodological and analytical expertise to help domain specialists to address their domain-specific problems that involve a new information source. Here, the domain specialists are following a traditional PCR approach and the ICR researchers are providing a supporting role. This help could be in terms of a) helping to identify specific solvable problems, or b) identifying or constructing methods appropriate for their identified research goals. The result could be a sole-authored article by the domain specialist or a joint-authored article. ICR5 is similar to ICR3 except that the initiative resides with the domain specialist.

ICR and PCR examples

Paper	Discussion	Type
Thelwall, M. (2008). Fk yea I swear: Cursing and gender in a corpus of MySpace pages, Corpora, 3(1), 83-107.	This is the result of an open-ended investigation into MySpace text, which lead to the observation of plentify swearing and triggered a solo ICR paper about swearing, research that is relevant to linguistics and was published (without a domain expert) in a linguistics journal.	ICR1
Thelwall, M., Sud, P., & Vis, F. (2012). Commenting on YouTube videos: From Guatemalan rock to El Big Bang. Journal of the American Society for Information Science and Technology,63(3), 616–629.	This was a descriptive investigation into comments in YouTube in conjunction with a video analysis expert, Farida Vis.	ICR2
-	There are no known examples of ICR3: although it seems like a good idea in the abstract, there are human factors involved which mean that it is difficult for a researcher to suggest research topics to other researchers within a different field.	ICR3
Thelwall, M. (2008). Social networks, gender and friending: An analysis of MySpace member profiles, Journal of the American Society for Information Science and Technology, 59(8), 1321-1330.	This is a descriptive analysis of MySpace member profiles - the analysis is relativley light on theory and is an attempt to give an overview of MySpace member profiles to aid future disciplinary research (e.g., in communication studies).	ICR4
Thelwall, M. & Hasler, L. (2007). Blog search engines. Online Information Review, 31(4), 467-479.	This is the result of open-ended investigations into blogs and blog searching, producing a general approach for exploiting blogs in social science research and advocating that other social scientists use the simple techniques to assess whether blog searching could be useful in their research area.	ICR4
Park, H. W. & Thelwall, M. (2008). Web linkage pattern and social structure using politicians’ websites in South Korea. Quality & Quantity, 42(6), 687-697.	This paper was the result of an approach by a political communication specialist (who was already an expert in hyperlink analysis).	ICR5
Thelwall, M., & Harries, G. (2004). Do better scholars’ web publications have significantly higher online impact? Journal of the American Society for Information Science and Technology, 55(2), 149-159.	This is a link analysis study, part of a series of attempts to determine whether hyperlink counts could be used to measure the online impact of academic research.	PCR
Thelwall, M. & Prabowo, R. (2007). Identifying and characterinsing public science-related fears from RSS feeds. Journal of the American Society for Information Science and Technology, 58(3), 379-390.	This is a blog analysis study, assessing whether blog analysis could reveal public science fears.	PCR

ICR Theoretical articles

Thelwall, M., Wouters, P., & Fry, J. (2008). Information-centred research for large-scale analysis of new information sources, Journal of the American Society for Information Science and Technology, 59(9), 1523-1527.

Thelwall, M. & Wouters, P. (2005). What’s the deal with the web/Blogs/the next big technology: A key role for information science in e-social science research? CoLIS 2005, Lecture Notes in Computer Science 3507, 187-199.