CATPAC & LIWC

1. CATPAC & LIWC Key output and findings D.K. & B.L.

2. How CATPAC is Used • Reads text to identify most important words • Can determine patterns of similarity • Produces simple frequency counts • The neural network is self-organizing • Finds patterns of usage between words • Uses clustering algorithms • Produces perceptual maps

3. CATPAC frequencies • TOTAL WORDS 300 THRESHOLD 0.000 • TOTAL UNIQUE WORDS 25 RESTORING FORCE 0.100 • TOTAL EPISODES 294 CYCLES 1 • TOTAL LINES 60 FUNCTION Sigmoid (-1 - +1) • CLAMPING Yes • DESCENDING FREQUENCY LIST ALPHABETICALLY SORTED LIST • CASE CASE CASE CASE • WORD FREQ PCNT FREQ PCNT WORD FREQ PCNT FREQ PCNT • --------------- ---- ---- ---- ---- --------------- ---- ---- ---- ---- • I 47 15.7 201 68.4 A 28 9.3 153 52.0 • A 28 9.3 153 52.0 ABOUT 6 2.0 42 14.3 • MY 19 6.3 89 30.3 ALL 6 2.0 39 13.3 • I'M 16 5.3 76 25.9 AM 14 4.7 86 29.3 • FOR 15 5.0 85 28.9 BE 13 4.3 75 25.5 • AM 14 4.7 86 29.3 CAN 6 2.0 39 13.3 • BE 13 4.3 75 25.5 FOR 15 5.0 85 28.9 • YOU 13 4.3 63 21.4 HAVE 9 3.0 54 18.4 • OUT 12 4.0 73 24.8 I 47 15.7 201 68.4 • KNOW 10 3.3 62 21.1 I'M 16 5.3 76 25.9 • HAVE 9 3.0 54 18.4 KNOW 10 3.3 62 21.1 • ME 9 3.0 51 17.3 LIFE 8 2.7 51 17.3 • ON 9 3.0 62 21.1 LOVE 8 2.7 46 15.6 • SOMEONE 9 3.0 59 20.1 ME 9 3.0 51 17.3 • WITH 9 3.0 58 19.7 MY 19 6.3 89 30.3 • LIFE 8 2.7 51 17.3 NO 6 2.0 41 13.9 • LOVE 8 2.7 46 15.6 NOT 8 2.7 45 15.3 • NOT 8 2.7 45 15.3 ON 9 3.0 62 21.1 • SHOULD 7 2.3 42 14.3 OUT 12 4.0 73 24.8 • SO 7 2.3 49 16.7 SHOULD 7 2.3 42 14.3 • ABOUT 6 2.0 42 14.3 SO 7 2.3 49 16.7 • ALL 6 2.0 39 13.3 SOMEONE 9 3.0 59 20.1 • CAN 6 2.0 39 13.3 WHAT 6 2.0 39 13.3 • NO 6 2.0 41 13.9 WITH 9 3.0 58 19.7 • WHAT 6 2.0 39 13.3 YOU 13 4.3 63 21.4

4. WARDS METHOD • A M H Y I N I A O S S W A N K W A M C L B S F L O • . Y A O ' O . B U O O I L O N H M E A O E H O I N • . . V U M T . O T . M T L . O A . . N V . O R F . • . . E . . . . U . . E H . . W T . . . E . U . E . • . . . . . . . T . . O . . . . . . . . . . L . . . • . . . . . . . . . . N . . . . . . . . . . D . . . • . . . . . . . . . . E . . . . . . . . . . . . . . • . . . . . . . . . . . . . . . . . . . . . . . . . • . . . . . . . . . . . . . . . . . . . . . . . . . • ^^^ . . . . . . . . . . . . . . . . . . . . . . . • ^^^^^ . . . . . . . . . . . . . . . . . . . . . . • ^^^^^^^ . . . . . . . . . . . . . . . . . . . . . • ^^^^^^^^^ . . . . . . . . . . . . . . . . . . . . • ^^^^^^^^^^^ . . . . . . . . . . . . . . . . . . . • ^^^^^^^^^^^^^ . . . . . . . . . . . . . . . . . . • ^^^^^^^^^^^^^ . . . . . . . . . . . . . ^^^ . . . • ^^^^^^^^^^^^^ . . . . . . . . . . . . . ^^^ . ^^^ • ^^^^^^^^^^^^^ . . . . . . . . . ^^^ . . ^^^ . ^^^ • ^^^^^^^^^^^^^ . . . . . . . ^^^ ^^^ . . ^^^ . ^^^ • ^^^^^^^^^^^^^ . . . . . ^^^ ^^^ ^^^ . . ^^^ . ^^^ • ^^^^^^^^^^^^^ ^^^ . . . ^^^ ^^^ ^^^ . . ^^^ . ^^^ • ^^^^^^^^^^^^^ ^^^ . . . ^^^ ^^^ ^^^ . . ^^^ ^^^^^ • ^^^^^^^^^^^^^ ^^^ . . . ^^^ ^^^ ^^^ ^^^ ^^^ ^^^^^ • ^^^^^^^^^^^^^ ^^^ . ^^^ ^^^ ^^^ ^^^ ^^^ ^^^ ^^^^^ • ^^^^^^^^^^^^^ ^^^^^ ^^^ ^^^ ^^^ ^^^ ^^^ ^^^ ^^^^^ • ^^^^^^^^^^^^^ ^^^^^ ^^^ ^^^ ^^^ ^^^^^^^ ^^^ ^^^^^ • ^^^^^^^^^^^^^ ^^^^^ ^^^ ^^^ ^^^ ^^^^^^^ ^^^^^^^^^ • ^^^^^^^^^^^^^ ^^^^^^^^^ ^^^ ^^^ ^^^^^^^ ^^^^^^^^^ • ^^^^^^^^^^^^^ ^^^^^^^^^ ^^^^^^^ ^^^^^^^ ^^^^^^^^^ • ^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^ ^^^^^^^ ^^^^^^^^^ • ^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^ • ^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ • ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Dendogram output

5. CATPAC 3-D Perceptual Map

6. Operating Issues with CATPAC • Exclude dictionary: must amend the default and save or create in correct format • Text input: separating multiple texts requires insertion of a slide barrier • Refining the exclude list and analysis settings can be a long, incremental process • The 3-D visualizing is cluttered for larger numbers of terms

7. Linguistic Inquiry andWord Count • Provide an effective method for studying emotional/cognitive/structural/process components present in individuals’ verbal and written speech • Calculates % of words that match of up to 84 dimensions • Generates an output that is readable by SPSS or Excel

8. LIWC / output variables • Text files, once formatted for entry, are processed for up to 84 output variables, including: • 17 standard linguistic dimensions (e.g., word count, percentage of pronouns, articles) • 25 word categories tapping psychological constructs (e.g., affect, cognition) • 10 dimensions related to "relativity" (time, space, motion) • 19 personal concern categories (e.g., work, home, leisure activities)

9. LIWC / How to… • For best results -> prepare text for analysis (adjust misspellings, inappropriate words, abbreviations) • Adjusting words can be tricky… e.g.: US -> U.S. • Sometimes used to analyze oral conversations/interviews -> transcribe speech to text -> dictionary includes some “nonfluencies” (e.g.: hm, uh, huh, um) • Analyzes data one file at a time • Files: TEXT or ASCII format! Can’t read word document • The longer the document, the better

10. LIWC / dictionaries • Only counts words that are in the dictionaries • default dictionary: Internal Pennebaker Dictionary -> 2300 words • But you can develop your own dictionary! • To create dictionary: choose “load new dictionary” from the “dictionary” menu • Dictionaries have to be plain text files

11. LIWC output with standard linguistic dimensions