Internet Addiction Studies: A Multiple Correspondence Analysis (MCA) of Research Articles Between 2000 and 2013
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
In this thesis, I conduct a Multiple Correspondence Analysis (MCA) on a set of 206 research articles on Internet Addiction (IA). To begin with, in section 1, I introduce the background, rationale, theoretical approach, method, and aim to investigate the field of IA research from a Sociology of Scientific Knowledge (SSK) perspective. Next, I stipulate two research questions: (RQ1) what constellations of theoretical approaches, methods, geography, and time can be found in IA research? and (RQ2) what do the constellations found in RQ1 say about IA research from a SSK perspective? In section 3, Theory, I therefore outline my theoretical rooting in the SSK in the Strong Programme for the study of scientific knowledge, followed by a description of the SSK itself and previous research that takes these theoretical approaches as its starting point. I then focus specifically on the IA research field's relationship with the paradigmatic history of the DSM and the concept of behavioral addictions, which sets the stage for my subsequent operationalization of IA studies in the categories Biometric, Psychometric, and Sociological IA studies. In section 4, Data, Code Scheme and Methods, I outline the data collection in terms of four phases of article exclusion, followed by a description of the methods and code scheme I used to code and analyze my data: content analysis and MCA. In addition, I discuss the ethical standpoints I have taken. In section 5, Results, I present the results of my study using a series of diagrams and bi-plots, which are then discussed in section 6. In short, I conclude that the state of IA research is best described as Normal science, with the caveat that the controversy of the IA concept may indicate that the field is in fact so polarized, scientists in the field may not even use the same terms.
Place, publisher, year, edition, pages
Internet Addiction, IA, Multiple Correspondence Analysis, MCA, Diagnostic and Statistical Manual of Mental Disorders, DSM, Strong Programme, Sociology of Scientific Knowledge, SSK, Normal Science, Extraordinary Science, Scientific Intellectual Movement, SIM
IdentifiersURN: urn:nbn:se:su:diva-118904OAI: oai:DiVA.org:su-118904DiVA: diva2:842539
Bergmark, Karin, Professor