Diction 5.0 Created by Roderick P. Hart Kimberly S. Cooper and Paul M. Palisin

About Diction Diction 5.0 contains a series of built-in dictionaries that search text documents for 5 main semantic features and 35 sub-features. Diction compares the results for each of the 40 dictionary categories to a "normal range of scores" determined by running more than 20,000 texts through the program.

About Diction, continued Users can compare their text to either a general normative profile of all 20,000-plus texts OR to any of 6 specific sub-categories of texts (business, daily life, entertainment, journalism, literature, politics, scholarship) that can be further divided into 36 distinct types. In addition, Diction outputs raw frequencies (in alphabetical order), percentages, and standardized scores; custom dictionaries can be created for additional analyses.

Features and sub-features 5 main semantic features –Activity, Optimism, Certainty, Realism and Commonality 35 sub-features –Numerical Terms, Ambivalence, Self-reference, Tenacity, Leveling Terms, Collectives, Praise, Satisfaction, Inspiration, Blame, Hardship, Aggression, Accomplishment, Communication, Cognition, Passivity, Spatial Terms, Familiarity, Temporal Terms, Present Concern, Human Interest, Concreteness, Past Concern, Centrality, Rapport, Cooperation, Diversity, Exclusion, Liberation, Denial and Motion

Running Diction We chose to run all Presidential inaugural addresses in Diction (1789 – 2009) Start by converting documents into text files (.txt) Data retrieved from Bartleby

Uploading documents into Diction Start a new project Add files to project

Processing in Diction Choose “selected files” or “all files” in the “Processing” menu

All files are in Diction ready to be processed

Process All Files in Diction

Processed data in Diction Adjust the windows to see more information about each file

Obama Output

Obama Character Frequency

Obama Dictionary Totals

Obama Dictionary Totals Cont’d.

Obama Insistence Score

Obama Variables

Diction Options Diction can focus its results based on the type of text.

Changing Normative Values For example, we could analyze individual presidential speeches in context of other campaign speeches.

Before changing normative values, the normal range for numerical terms was between 0.30 and

To access Diction data Go to My Computer  C drive  Program Files  Diction  Data  Research.num Data is saved there by default.

Importing Diction data into SPSS

Imported data in SPSS Moving data from Diction to an analysis program like SPSS allows you to analyze text data more rigorously

With SPSS, data can be examined and analyzed in many ways