Using TextMind and LIWC
software, we calculated emotional word frequency and classified the words into 20 different categories and subcategories (Pennebaker & Booth, 2007): social processes (family, friends, human beings), emotional processes (positive emotions: cheerfulness, enthusiasm, self-confidence, joy; negative emotions: anxiety, anger, sadness), cognitive processes (insight, causality), perceptual processes (time), personal concerns (work, achievement, religion, death), and psychology.
A series of paired-samples t-tests were conducted to evaluate whether advice seekers and givers differed in regard to the LIWC
variables mentioned previously.
Alor-Hernandez, <<A study on LIWC
categories for,>> Journal of Information Science, vol.
Pennebaker et al., The Development and Psychometrics Properties of LIWC2007, LIWC
, http://www.liwc.net/LIWC2007LanguageManual.pdf (last visited Mar.
Individual tweets were contextually analyzed using the LIWC
software (Pennebaker, Francis, & Booth, 2001) to explore effects of values communication and emotions.
, which I mentioned earlier, seems more promising, but it too is not perfect, in part because its dictionaries were not designed for legal texts.
Participants' written responses were analyzed using Linguistic Inquiry and Word Count (LIWC
), a standardized, quantitative method for categorizing linguistic responses (Pennebaker & Francis, 1996).
use the famous Linguistic Inquiry and Word Count (LIWC
) software  to build their features for the reviews.
Stirman used Linguistic Inquiry Word Count (LIWC
) computer software while West and Martindale used COUNT and LEXSTAT.
The computer text analysis program called Linguistic Inquiry and Word Count, or LIWC
(Pennebaker et al., 2001) was used to analyze the letters.
He started with the Linguistic Inquiry and Word Count (LIWC
) program, a decades-old algorithm developed by psychologist James Pennebaker and colleagues that can determine people's psychological states and personality traits by analyzing their speech or writing.
Consistent with previous studies (Brett et al., 2007), we utilized CATA to determine narratives' negative emotional content using the negative emotional word Linguistic Inquiry and Word Count (LIWC
) dictionary (Pennebaker, Francis, & Booth, 2001).