Content Analysis Overview Shin Dig Webinar March 15

Content Analysis: Overview Shin. Dig Webinar, March 15, 2018, 7 p. m. EDT Liz Johnston, Ed. D. Erik Bean, Ed. D.

Agenda • Overview • Introductions, Liz, Erik • Content Analysis Rigor: Reliability • Content Analysis Design, Quantitative, Qualitative • Examples • Resources • Questions

Content is Everywhere

Overview of Content Analysis • MOST USED FOR COMPARING OR BENCHMARKING MEDIA CONTENT IN THE HUMANITIES FIELDS • Quantitative Content Analysis: instances of words, images, measurements, and published pieces, for example, are counted and compared to one another based on size, frequency, prominence (how likely they would be seen by the target audience) and by whatever research question is posed. • Qualitative Content Analysis: inductive reasoning for meaning as well as size, frequency, and prominence

Flexibility • “For every question of interest: a universe of textual data exists from which a representative sample can be drawn”(p. 14, Stepchenkova, Kirilenko, & Morrison) • Destination Images analyzed for meaning in tourism research Stepchenkova, S. , Kirilenko, A. , Morrison, A. Facilitating Content Analysis in Tourism Research. SAGE Secondary Data Analysis. SAGE Publications Ltd. London: SAGE Publications Ltd.

We Are Available to Help Dr. Bean and Dr. Johnston are happy to assist those who may need help : • Developing a rigorous coding book of definitions which must be in place before any analysis starts. • Thinking about design possibilities. • Finding texts you might find useful.

Methodologist Introduction: Liz Johnston, Qualitative Content Analysis • Dissertation: observations of frequency. • I learned content analysis in application. • I read methodologists and published articles • I had some good coaches that I could call on during the process. Dr. Kebritchi was one!

Methodologist Introduction: Erik Bean, Quantitative Content Analysis • I was taught content analysis under the tutelage of Stephen Lacy, Ph. D. , Michigan State University Professor of Economic journalism, prolific, and noted method author. • Much of the success relies on operationalizing key terms and developing a rigorous coding book of study definitions. • Used in journalism, social sciences when documenting size, prominence, and instances.

Content Analysis Design: Quanti, Qualti • Top Down-Deductive-start with a principle and apply • Bottom Up-Inductive-begin with the data and develop a principle

Qualitative Rigor/Credibility Qualitative Credibility: Logical consistency between: – Theory derived from the literature. – Design is aligned with research question. Visibility promotes credibility: -- Broad sample selection with limits explained -- Purposive sampling-select individuals with knowledge of research topic Detailed, explicit procedures for collecting and analyzing data: -- Member checking or other steps -- Inter-rater reliability/piloting (Twining, 2017).

Content Analysis: Design Capacity and Advantages • Flexible design- analysis of human communication (often public) – Stands alone – Combines with other designs • Flexible access – Visual as well as verbal analysis – Access to hard to reach populations – Unobtrusive

Content Analysis: Design Capacity and Advantages • Uses available data: – What has already been published? • Examples-posters on a wall • Newspaper articles • Blogs • Letters or emails • Anything that indicates direct or indirect traces of human communication

Quantitative Example: • Destination images in tourism research – Combined inductive and deductive approaches – Data collection through interviews, surveys – Coding dictionaries – Frequency counts – Statistical analysis based on word matrix Stepchenkova, S. , Kirilenko, A. , Morrison, A. Facilitating Content Analysis in Tourism Research. SAGE Secondary Data Analysis. SAGE Publications Ltd. London: SAGE Publications Ltd.

Quantitative Examples Continued: Bean, E. (2017). An academy customer experience benchmark observation. Internet Learning Journal, 5(1), 17 -31. Bean, E. (2015). Assessing the degree of homogeneous online teaching textbook Infancy from 1999 to 2007 using the immediacy principle. Internet Learning Journal, 4(1). 88 -125.

Qualitative Example – Content Analysis within Case Study – RQ: How did school leaders construct meaning from spending the day shadowing a student? – Data sources: Blogs, policy documents, Interviews with school leaders. Hartman, R. , Johnston, E. , & Hill, M. , (2017) Empathetic design: A sustainable approach to school change. Discourse and Communication for Sustainable Education http: //www. qualitativeresearch. net/index. php/fqs/article/view/1089/2385

Mixed Method Example • A content analysis of the mission statements of colleges of engineering to map inductively derived codes with the Engineering Criteria (EC 2000) outcomes and to test if any of the codes were significantly associated with institutions with reasonably strong representation of women. Creamer, E. G. , & Ghoston, M. (2013). Using a mixed methods content analysis to analyze mission statements from colleges of engineering. Journal of Mixed Methods Research, 7(2), 110 -120. doi: 10. 1177/1558689812458976

Convention Content Analysis Example: • RQ: What experiences do family members of people with dementia share about use of music? • Data Sources: 35 Family member comments posted at Music and Memory site (Hsiu-Fang, H. & Shannon, S. , (2005). Three approaches to qualitative content analysis. Qualitative Health Research. 15 (9), 1277 -1288. doi: 10. 1177/1049732305276687)

Qualitative Unobtrusive Example: Qualitative; unobtrusive and uses inductively derived coding: Johnston, E. , Rasmusson, X. , Foyil, B. , & Shopland P. , (2017) Witnesses to transformation: Family member experiences providing individualized music to their relatives with dementia. Cogent Education. Taylor and Francis Publishing http: //dx. doi. org/10. 1080/2331186 X. 2017. 1362888

Qualitative Unobtrusive Example: • The purpose of this study was to explore the experiences and gain a better understanding of young adults affected by cancer by examining their online narratives (also known as Web logs or blogs) • Conclusions: The Internet provides young cancer patients with a space in which to express themselves and to share experiences with those who are of similar age and in similar situations. Kim, B. , & Gilhma, D. , (2013). The experience of young adult cancer patients described through online narratives. Cancer Nursing, 36(5) DOI: 10. 1097/NCC. 0 b 013 e 318291 b 4 e 9

Resources • Creswell, J. W. , Clark, V. L. , Gutmann, M. L. , & Hanson, W. E. (2003). Advanced mixed methods research designs. In A. Tashakkori & C. Teddlie (Eds. ), Handbook of mixed method research in social and behavioral research (pp. 209 -240). Thousand Oaks, CA: Sage. • Hsiu-Fang, H. , & Shannon, S. (2005) Three approaches to qualitative content analysis. Qualitative Heath Research. 15: 1277 -1288, doi: 10. 1177/1049732305276687 • Mayring, P. (2000) Qualitative Content Analysis. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, [S. l. ], v. 1, n. 2, june 2000. ISSN 1438 -5627.

Resources • Riffe, D. , Fico, F. , & Lacy, S. (2005). Analyzing media messages: Using quantitative content analysis in research (2 nd ed. ). Mahwah, NJ: Lawrence Erlbaum. • Stepchenkova, S. , Kirilenko, A. , Morrison, A. Facilitating Content Analysis in Tourism Research. SAGE Secondary Data Analysis. SAGE Publications Ltd. London: SAGE Publications Ltd. • Twining, P. (2017) Some guidance on conducting and reporting qualitative studies. Computers & Education; 106. http: //dx. doi. org/10. 1016/j. compedu. 2016. 12. 002 • Yalçın, S. , Çiğdem. Y. , & Dibek, M. (2015). Content analysis of papers published in educational journals with high impact factors. Education & Science / Egitim ve Bilim, 40(182), 1 -28. doi: 10. 15390/EB. 2015. 4868

NOTES • This article proposes a methodological approach to analyzing multiple files of textual data typical in tourism studies in a transparent, replicable, and effective way. The approach proceeds with data preparation, identification of key variables, obtaining the word-frequency matrix, and subsequent dimensional reduction of word-frequency data. Obtaining a matrix of word frequencies from multiple units of qualitative data allows more sophisticated statistical analyses of data and, ultimately, hypothesis testing. The approach uses an efficient combination of two computer programs, CATPAC and WORDER; however, the methodology is not dependent on this particular software tandem. Other programs that perform the same functions can be used, and the choice, as always, is with the researcher. The objective of the article is to show that the proposed methodology is firmly grounded in theory and practices of content analysis and is both simple and efficient enough to facilitate statistical data analysis in tourism studies.

Questions? Content Analysis Method Dr. Erik Bean (Quantitative Content Analysis) deadline@email. phoenix. edu Dr. Liz Johnston (Qualitative Content Analysis) ljohnston@email. phoenix. edu