A computer-assisted approach to filtering large numbers of documents for media analyses

International Journal of Social Research Methodology

Volumn 16, Issue 1, 2013, Pages 13-30

  Voth, James ^a   Sawatzky, Richard ^b   Ratner, Pamela A ^c   Young, Mary Lynn ^c   Repta, Robin ^c   Haines Saah, Rebecca ^c   Johnson, Joy L ^c  

^a Intogrey   (Canada)

^b TRINITY WESTERN UNIVERSITY   (Canada)

^c UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

computer assisted; document filtering; media analysis; precision; selection bias

Indexed keywords

EID: 84873641180     PISSN: 13645579     EISSN: 14645300     Source Type: Journal    
DOI: 10.1080/13645579.2011.645700     Document Type: Article

References (27)

1. Baeza-Yates, R. and Ribeiro-Neto, B. 2011. Modern information retrieval: The concepts and technology behind search, 2nd ed., New York, NY: Addison Wesley.
2. Cooper, H. 2009. Research synthesis and meta-analysis, Thousand Oaks, CA: Sage.
3. Dauvergne, M. 2009. Trends in police-reported drug offences in Canada. Juristat, 29(2)
4. Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K. and Harshman, R. 1990. Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6): 391-407. doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9
5. Elgar, F.J., Phillips, N. and Hammond, N. 2011. Trends in alcohol and drug use among Canadian adolescents, 1990-2006. Canadian Journal of Psychiatry, 56(4): 243-247.
6. Fischer, B., Rehm, J. and Hall, W. 2009. Cannabis use in Canada: The need for a 'public health' approach. Canadian Journal of Public Health-Revue Canadienne De Sante Publique, 100(2): 101-103.
7. Jones, C. and Hathaway, A.D. 2008. Marijuana medicine and Canadian physicians: Challenges to meaningful drug policy reform. Contemporary Justice Review, 11(2): 165-175. doi:10.1080/10282580802058429
8. Jordan, A.B. and Manganello, J. 2009. "Sampling and content analysis: An overview of the issues". In Media messages and public health: A decisions approach to content analysis, Edited by: Jordan, A.B., Kunkel, D., Manganello, J. and Fishbein, M. 53-66. New York, NY: Taylor and Francis.
9. Jurafsky, D. and Martin, J.H. 2009. Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition, 2nd ed., Upper Saddle River, NJ: Pearson Prentice Hall.
10. Kolbe, R.H. and Burnett, M.S. 1991. Content-analysis research: An examination of applications with directives for improving research reliability and objectivity. Journal of Consumer Research, 18(2): 243-250.
11. Krippendorff, K. 2004. Content analysis: An introduction to its methodology, 2nd ed., Thousand Oaks, CA: Sage.
12. Malm, A.E. and Tita, G.E. 2007. A spatial analysis of green teams: A tactical response to marijuana production in British Columbia. Policy Sciences, 39(4): 361-377. doi:10.1007/s11077-006-9029-0
13. Manin, D. 2008. Zipf's Law and avoidance of excessive synonymy. Cognitive Science, 32(7): 1075-1098. doi:10.1080/03640210802020003
14. Muschert, G.W. 2007. The Columbine victims and the myth of the juvenile superpredator. Youth Violence and Juvenile Justice, 5(4): 351-366. doi:10.1177/1541204006296173
15. Navigli, R. 2009. Word sense disambiguation: A survey. ACM Computing Surveys, 41(2): 10:11-10:69. doi:10.1145/1459352.1459355
16. Neuendorf, K. 2002. The content analysis guidebook, Thousand Oaks, CA: Sage.
17. Neuendorf, K. 2011. Content analysis: A methodological primer for gender research. Sex Roles, 64(3): 276-289. doi:10.1007/s11199-010-9893-0
18. Riffe, D., Aust, C.F. and Lacy, S.R. 2009. "Effectiveness of random, consecutive day and constructed week sampling". In The content analysis reader, Edited by: Krippendorff, K. and Bock, M.A. 54-59. Thousand Oaks, CA: Sage.
19. Riffe, D., Lacy, S. and Fico, F. 2005. Analyzing media messages: Using quantitative content analysis in research, 2nd ed., Mahwah, NJ: Lawrence Erlbaum.
20. Rock, M. 2005. Diabetes portrayals in North American print media: A qualitative and quantitative analysis. American Journal of Public Health, 95: 1832-1838. doi:AJPH.2004.049866
21. Sanderson, M. (2008). Ambiguous queries: Test collections need more sense. Paper presented at the Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, Singapore.
22. Skelton, C. (2004, September 25). Police fear gang war over pot: Price drop expected to ignite violence between crime groups, The Vancouver Sun, p. C2.
23. Spasic, I., Ananiadou, S., McNaught, J. and Kumar, A. 2005. Text mining and ontologies in biomedicine: Making sense of raw text. Briefings in Bioinformatics, 6(3): 239-251. doi:10.1093/bib/6.3.239
24. Stryker, J.E., Wray, R.J., Hornik, R.C. and Yanovitzky, I. 2006. Validation of database search terms for content analysis: The case of cancer news coverage [Article]. Journalism & Mass Communication Quarterly, 83(2): 413-430.
25. Turdakov, D. 2010. Word sense disambiguation methods. Programming and Computer Software, 36(6): 309-326. doi:10.1134/s0361768810060010
26. Unicode® Consortium. (2009). Unicode® Standard Annex #29: Unicode® Text Segmentation. In M. Davis (Ed.), Mountain view. CA: Author. Retrieved fromhttp://www.unicode.org/reports/tr29/tr29-15.html
27. White, H.D. 2009. "Scientific communication and literature retrieval". In The handbook of research synthesis, 2nd ed., Edited by: Cooper, H. and Hedges, L.V. 51-71. New York, NY: Russell Sage.