Roel Popping, Department of Sociology, University of Groningen

Computer-assisted text analysis, and the relevance of decision making and text mining

Course Content
An overview will be presented of recent developments in the field of quantitative computer-assisted text analysis as applied in the social sciences (sociology, psychology, political science). This is different from the approach by investigators from the field of computational science. We start from the traditional content analysis or instrumental thematic text analysis (Holsti, Krippendorff, Weber). Here the investigator looks in most situations at characteristics of the substance of the texts (trace the development of scholarship; show differences in communication content between countries or over time). This is done by looking at the (co-) occurrence of concepts. First this occurrence of concepts was investigated from the perspective of the investigator (instrumental view), today it is also considered from the perspective of the sender of the message (representational view). Especially this view is not only applied in the thematic approach, but also in the semantic (which considers relations between concepts) and the network approach (text is transferred into networks). Special attention will be given to the relation with qualitative research and to reliability issues. Later on the decision making within text analysis will be elaborated, most of all focusing on the semantic analysis. Here one runs into the problems of ambiguity and of intended meaning of texts. In the final presentation thoughts will be presented on how text mining might be used here.

Reading

• Popping, R. & Roberts, C. W. (2009). “Coding issues in semantic text analysis.” Field Methods, 21 (3): 244-264.
  
  
• Roberts, C. W. (2000). A conceptual framework for quantitative text analysis. Quality & Quantity, 34 (3): 259–274.

References

• Alexa, M. and Zuell, C. (2000). Text analysis software: commonalities, differences and limitations: the results of a review. Quantity & Quality, 34: 299–321.
  
  
• Bauer, M.W. (2000). “Classical Content Analysis: a Review,” in Bauer, M.W. & Gaskell, G. (eds.) Qualitative Researching with Text, Image and Sound. London: Sage, pp. 131-151.
  
  
• Carley, K.M. (1993) Coding Choices for Textual Analysis: A Comparison of Content Analysis and Map Analysis. Sociological Methodology, 23: 75-126.
  
  
• Danielson, W.A. &Lasorsa, D.L. (1997) Perceptions of social change: 100 Years of front page content in The New York Times and The Los Angeles Times, in: Roberts, C.W. Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts. Mahwah, NJ: Lawrence Erlbaum, 103-115.
  
  
• Franzosi, R. (1994) ‘From words to numbers: A set theory framework for the collection, organization, and analysis of narrative data’, in P.V. Marsden (ed.), Sociological Methodology 1994. Oxford: Blackwell. pp. 105–36.
  
  
• Franzosi, R. (1998) Narrative Analysis-or Why (and How) Sociologists Should Be Interested in Narrative. Annual Review of Sociology, 24: 517-554.
  
  
• Gottschalk, Louis A. (1995) Content Analysis of Verbal Behavior: New Findings and Computerized Clinical Applications. Hillsdale, NJ: Lawrence Erlbaum Associates.
  
  
• Hak, T. &Bernts, T. (1996) Coder Training: Theoretical Training or Practical Socialization. Qualitative Sociology, 19 (2): 235-257.
  
  
• Hogenraad, R., Bestgen, Y. &Nysten, J.L. (1995) Terrorist rhetoric: texture and architexture, in: Nissan, E. & Schmidt, K. From Information to Knowledge: Conceptual and Content Analysis by Computer. Oxford: Intellect, 48-59.
  
  
• Holsti, O.R. (1969). Content Analysis for the Social Sciences and Humanities. London: Addison Wesley.
  
  
• Kleinnijenhuis, J., De Ridder, J.A. &Rietberg, E.M. (1997) Reasoning in economic discourse: An application of the network approach to the Dutch press, in: Roberts, C.W. Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts. Mahwah, NJ: Lawrence Erlbaum, 191-207.
  
  
• Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology. Sage, Thousand Oaks, CA, 2nd edition.
  
  
• Laver, M. and Garry, J. (2000). Estimating policy positions from political texts. American Journal of Political Science, 44 (3): 619–634.
  
  
• Lowe, W. (2008). Understanding Wordscores. Political Analysis, 16 (4): 356-371.
  
  
• Markoff, John, Shapiro, Gilbert and Weitman, Sasha R. (1974) ‘Toward the integration of content analysis and general methodology’ in D.R. Heise (ed.), Sociological Methodology 1975. San Francisco: Jossey Bass. 1–58.
  
  
• Miller, M. M (1997) Frame mapping and analysis of news coverage of contentious issues. Social Science Computer Review, 15 (4): 367–78.
  
  
• Namenwirth, J.Z. (1969) Marks of Distinction: An Analysis of British Mass and Prestige Newspaper Editorials. American Journal of Sociology,74 (4): 343-360.
  
  
• Neuendorf, K. A. (2002). The Content Analysis Guidebook. Thousand Oaks, CA: Sage.
  
  
• Pennebaker, J. W. and Chung, C. K. (2008). Computerized text analysis of al-Qaeda transcripts, in Krippendorf, K. and Bock, M. A., (eds), The Content Analysis Reader. Sage.
  
  
• Popping, R. (2000) Computer-assisted Text Analysis. London: Sage.
  
  
• Popping, R. (2010). Ag09. A Computer Program for Interrater Agreement for Judgments. Social Science Computer Review, , 28 (3): 391-396.
  
  
• Popping, R. & Roberts, C. W. (2009). Coding issues in semantic text analysis. Field Methods, 21 (3): 244-264.
  
  
• Roberts, C.W. (1989) Other Than Counting Words: A Linguistic Approach to Content Analysis. Social Forces, 68 (1): 147-177.
  
  
• Roberts, C. W. (2000). A conceptual framework for quantitative text analysis. Quality & Quantity, 34 (3): 259–274.
  
  
• Roberts, C.W., Popping, R. & Pan, Y. (2009). Modalities of democratic transformation: Forms of public discourse within Hungary’s largest newspaper, 1990-1997. International Sociology, 24 (4): 498-525.
  
  
• Scott, W.A. (1955) ‘Reliability of content analysis: The case of nominal scale coding’, Public Opinion Quarterly, 19 (3): 321-5.
  
  
• Schonhardt-Bailey, C. (2005). Measuring ideas more effectively: An analysis of Bush and Kerry’s national security speeches. PS: Political Science and Politics, 38: 701-711
  
  
• Schrodt, P.A. &Gerner, D.J. (1997) Empirical indicators of crisis phase in the Middle East, 1979-1995. Journal of Conflict Resolution, 41 (4): 529-552.
  
  
• Shapiro, G. &Markoff, J. (1997) A matter of definition, in: Roberts, C.W. Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts. Mahwah, NJ: Lawrence Erlbaum, 9-31.
  
  
• Stone, P. & Brody, R. (1970) Modeling opinion responsiveness to daily news: The public and Lyndon Johnson 1965-1968. Social Science Information, 9 (1): 95-123.
  
  
• Van Cuilenburg, J.J., Kleinnijenhuis, J. & De Ridder, J.A. (1988) Artificial intelligence and content analysis: Problems of and strategies for computer text analysis. Quality & Quantity, 22 (1): 65-97.
  
  
• Weber, R.P. (1990). Basic Content Analysis. Beverly Hills, CA: Sage.
  
  
• Whissell, C. (1996) Traditional and Emotional Stylometric Analysis of the Songs of the Beatles Paul McCartney and John Lennon. Computers and the Humanities, 30 (3): 257-265.

Biosketch
Roel Popping is at the Department of Sociology at the University of Groningen, The Netherlands. His research is on historical shifts in public opinion, values, and scientific knowledge, primarily within the context of post-1989 Central and Eastern Europe. His book, Computer-assisted Text Analysis, was published by Sage in 2000. He has articles in International Sociology 2009 (Modalities of democratic transformation: Forms of public discourse within Hungary’s largest newspaper, 1990–1997), Field Methods 2009(Coding Issues in Modality Analysis), Quality & Quantity 2010 (Some Views on Agreement to Be Used in Content Analysis Studies), ans Social Science Computer Review 2010 (Ag09. A computer program for interrater agreement for judgements).

© 2010 - 2011 Lipari School
webmaster: C. Catalano