MCCAlite

1. Minnesota Contextual Content Analysis MCCAlite Jeff Spicer & Matthew Egizii

2. MCCAlite • Created by Donald McTavish & Kenneth Litkowski • Department of Sociology, University of Minnesota • Full version only operates on a Control Cyberdata 174 computer at the University of Minnesota

3. Conceptual Dictionary 116 categories used to organize word meaning Examine patterns of emphasized ideas in text as well as the social context or underlying perspective reflected in the text. MCCAlite • Used to analyze: • Scripts • Transcripts • Screenplays • Open-ended items • Potentially Likert type scales

4. Preparation/Formatting • Choose an Input file • As usual, .txt is preferred • If you use the full version, it can alsotake .sav (its own file type) • {MCCALite cannot save output!} • [Correction: it has been updatedto give output, but our lab does not have this version!] • Frequent Words File • Default is FREQWDS.TXT • This is used to exclude certain words from analysis • Not recommended by the programmers! • Throws off weightings

5. Preparation/Formatting cont’d

6. Preparation/Formatting cont’d

7. Preparation/Formatting cont’d

8. Preparation/Formatting cont’d • Text Separator • $ means the end of a body of text. • This is really important. • MCCALite can’t process E-/C-Scores without it! • Text Title • Marks the word/text as a unit of analysis. • Bracket the word/text with “=“ • For example: • = Horatio = • would track every time Horatio speaks • ALSO VERY IMPORTANT • Can be time consuming…*sigh*

9. Preparation/Formatting cont’d

10. Word Accounting Total # of Words Total Words Categorized % categorized % of unique words % of categorized unique words Word Length Mean Standard Deviation Low/High Word Analysis

11. Words by Category/Frequency • Select a text group from the drop down to examine their word use. • This shows ONLY that text group. • Shown @ rightis “SLUG LINE” • Frequency can be set to a minimum in the drop down box above. • Shown @ right set to {5}

12. Key Words In Context Lines up concordances in the text to observe them in context. KWIC

13. C-Scores • Measures social context across 4 main categories • Traditional • Focus on norms and expectations • Practical • Focus on successful (efficient) goal accomplishment • Emotional • Focus on personal involvement, comfort, enjoyment or leisure • Analytic • Focus on objectivity, curiosity, or interest

14. C-Scores cont’d • Scores (Weighted) • Scaled for each text with values of –25 to +25

15. C-Scores cont’d • Plots (Weighted) • Helps compare the profiles visually

16. C-Scores cont’d • Scores (Raw) • Un-normalized scores, sum to 0, but aren’t scaled. • Plots (Raw) • As with weighted, these help visualize the scores. • {Not shown, we figure you get the picture.}

17. C-Scores cont’d • Distance Matrix • Euclidian distance between C-scores of each pair of text groups in the input file. • Texts that are similar have smaller values. • E-scores have this table too!

18. E-Scores • Show emphasis on groups of idea categories formed from the 116 individual categories. • Scores are “Normed” against expected usage. • This demonstrates over-emphasis and under-emphasis. • It is a computed score based on probability.

19. E-Scores cont’d • High-Categories • 23 super-categories grouped together from the initial 116

20. E-Scores cont’d • Selected Plots • Allows you to choose a specific category’s emphasis to plot, by Text Group. • Not the plot of the High Categories, but the individual ones.

21. E-Scores cont’d • Difference Analysis • Indicates how different the selected Text Group is from all other Text Groups (or characters, etc.) • Listed by category

22. E-Scores cont’d • Diagnostic Groups • 43 combinations of categories • Set up as scales for further analysis • {pretty sure about that} • This is the interesting bit

23. The Searchers • We decided to demonstrate this software using this film: • Characters: • Ethan Edwards (Wayne) & 5 others • Also, created “SLUG LINE” • Scene heading, actions, transitions, etc. • Plot: • “As a Civil War veteran spends years searching for a young niece captured by Indians, his motivation becomes increasingly questionable.” • Length: • Approximately 8 pages of screenplay. • Reason for excerpt: • Contained dialog and more than one character. • This was entirely exploratory • {remember, data can’t be saved!}