Linguistic Inquiry and Word Count (LIWC)

Count (LIWC( is a powerful text analysis tool used to examine the psychological and social dimensions of language. Developed through decades of research, LIWC can analyze text to reveal insights into emotions, thinking styles, social concerns and more.

1. Brief Overview of Linguistic Inquiry and Word Count (LIWC)

2. Linguistic Inquiry and Word Count ( LIWC ( is a powerful text analysis tool used to examine the psychological and social dimensions of language. Developed through decades of research, LIWC can analyze text to reveal insights into emotions, thinking styles, social concerns and more. Definition of the term (LIWC)

3. Key Features of LIWC Psychological Insights: Analyzes language to understand psychological states, emotions, thinking styles, and social concerns. Extensive Dictionaries: Includes More than 80 linguistic and psychological categories. Percentage Calculation: Calculates the percentage of words in a text that match each dictionary category. Hierarchical Categories: Categories are organized hierarchically, and words can belong to multiple categories. Contextual Accuracy: Generally reliable, especially with longer texts, though it can sometimes misinterpret words due to context. Probabilistic Models: Uses probabilistic models to improve accuracy in identifying and counting words .

4. LIWC analyzes emotions by categorizing words into various emotional dimensions. Here’s a brief overview of how it works: Word Categorization : LIWC has a dictionary that includes words associated with different emotions. For example, words like “happy,” “joy,” and “love” are categorized under positive emotions, while words like “sad,” “angry,” and “fear” fall under negative emotions. Frequency Counting: It counts the frequency of these emotion-related words in a given text. This helps in determining the overall emotional tone. Contextual Understanding : While LIWC primarily focuses on word frequency, it also considers the context to some extent. For instance, it can differentiate between “I am not happy” and “I am happy” by analyzing the surrounding words. Output Metrics : The tool provides various metrics, such as the percentage of words related to positive or negative emotions, which can be used to gauge the emotional content of the text. How does LIWC analyze emotions?

5. Preparing group interaction data for analysis in LIWC involves several key steps to ensure accurate and meaningful results. Here’s a Steps to Prepare Group Interaction Data for LIWC Analysis : Transcription: Accurate Transcripts: Ensure that all group interactions are transcribed accurately. This includes capturing all spoken words, pauses, and any relevant non-verbal cues. Consistency: Maintain consistency in transcription conventions, such as how you denote pauses, interruptions, and overlapping speech . Preparing Group Interaction Data for Analysis in LIWC

6. Data Cleaning: Remove Irrelevant Data: Eliminate any non-relevant text, such as background noise descriptions or unrelated conversations. Standardize Formatting: Ensure that the text is uniformly formatted. This includes consistent use of punctuation, capitalization, and spacing . Preparing Group Interaction Data for Analysis in LIWC

7. Segmentation : Divide by Speaker: Segment the text by speaker to analyze individual contributions to the group interaction. Time Intervals: If analyzing changes over time, segment the text into appropriate time intervals (e.g., every 5 minutes). Preprocessing for LIWC: Convert to Plain Text: Ensure the transcripts are in plain text format (.txt) as LIWC requires this format for analysis. Check for Special Characters: Remove or replace any special characters that might interfere with LIWC’s processing . Preparing Group Interaction Data for Analysis in LIWC

8. Running LIWC Analysis: Load Text Files: Load the prepared text files into LIWC. Select Categories: Choose the relevant LIWC categories for your analysis, such as emotional tone, cognitive processes, or social dynamics. Run Analysis: Execute the analysis to generate the LIWC output, which includes various linguistic and psychological metrics. Post-Processing: Combine Results: If you have multiple files or segments, combine the LIWC results into a single dataset for comprehensive analysis. Statistical Analysis: Use statistical software to analyze the LIWC output, looking for patterns and correlations in the group interaction data. Preparing Group Interaction Data for Analysis in LIWC

9. THANK YOU