Key output and findings D.K. & B.L. CATPAC & LIWC Key output and findings D.K. & B.L.
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
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 CATPAC frequencies
Dendogram output 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
CATPAC 3-D Perceptual Map
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
Linguistic Inquiry and Word 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
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)
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
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
LIWC output with standard linguistic dimensions