C.18 LIWC Lexical Word Counts

1. Feature Name

LIWC and other Lexical Features (Word Counts)

2. Literature Source (Serial Number, link)

C.18, My Team Will Go On: Differentiating High and Low Viability Teams through Team Interaction

3. Description of how the feature is computed (In Layman’s terms)

The feature counts how many instances a word from the LIWC corpus was used in a given text message. The value is then normalized as a rate of counts per 100 words.

4. Algorithms used (KNN, Logistic Regression etc.)

N/A

5. ML Inputs/Features

N/A

6. Statistical concepts used

N/A

7. Pages of the literature to be referred to for details

p.9 of paper

In addition, the following papers are cited in C.18, related to LIWC:

Swapna Somasundaran and Janyce Wiebe. 2010. Recognizing stances in ideological on-line debates. In Proceedings of the NAACL HLT 2010 workshop on computational approaches to analysis and generation of emotion in text. Association for Computational Linguistics, 116–124.

Glen Coppersmith, Mark Dredze, and Craig Harman. 2014. Quantifying mental health signals in Twitter. In Proceedings of the workshop on computational linguistics and clinical psychology: From linguistic signal to clinical reality. 51–60.

Yla R Tausczik and James W Pennebaker. 2010. The psychological meaning of words: LIWC and computerized text analysis methods. Journal of language and social psychology 29, 1 (2010), 24–54.

8. Any tweaks/changes/adaptions made from the original source

N/A