The development and psychometric properties of LIWC2007

By James W. Pennebaker, Cindy K. Chung, Molly Ireland, Amy L. Gonzales, R. Booth. 2007

970 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8fb7d85cefa1a0dbc5cec05f2c052c58ced71390

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Citations in the corpus

Computationally Detecting and Quantifying the Degree of Bias in Sentence-Level Text of News Stories (2015, unknown): “The Linguistic Inquiry and Word Count (LIWC) [16] is text analysis software designed for studying the various emotional, cognitive, structural, and process components present in text samples [17].”
The SEMAINE corpus of emotionally coloured character interactions (2010, methodology): “Linguistic analysis of these texts is conducted using the Linguistic Inquiry and Word Count (LIWC, [14]) program providing an additional 68 linguistic dimensions for the global conversation, user speech and operator speech for each clip.”
Can Facebook Predict Stock Market Activity (2013, unknown): “My inclusion of these variables is motivated by evidence from the psychology literature that nearly 40 percent of mood variation can be explained by the weather (Persinger and Levesque, 1983).(19) Following Saunders (1993), I collect weather data for New York City from the National Climatic Data Cen”
Filter Bubbles, Echo Chambers, and Online News Consumption (2016, unknown): “We augment this list with a set of 39 first and third person pronouns (Pennebaker et al., 2007, 2001), since opinion pieces—unlike descriptive articles—are often written in the first person , and including such pronouns has been shown to improve performance (Glover et al., 2001).”
The psychology of job loss: using social media data to characterize and predict unemployment (2016, methodology): “For broader validation of LIWC, we refer the reader to [34] or to the LIWC website (liwc.”
From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses (2015, methodology): “We examine differences in usage patterns of categories from the Linguistic Inquiry Word Count (LIWC), a widely used psychometrically validated tool for psychology-related analysis of language (Pennebaker et al., 2007; Pennebaker et al., 2001).”
Syntactic Stylometry for Deception Detection (2012, unknown): “Most are based on dictionary-based word counting using LIWC (Pennebaker et al., 2007) (e.g., Hancock et al. (2007), Vrij et al. (2007)), while some recent ones explored the use of machine learning techniques using simple lexico-syntactic patterns, such as n-grams and part-of-speech (POS) tags…”
The sociality of personal and collective nostalgia (2019, methodology): “Adding to prior findings, the LIWC revealed that nostalgic (vs. control) narratives featured a lower frequency of firstperson singular pronouns, indicating decreased self-focus, and a higher frequency of first-person plural pronouns, indicating a stronger emphasis on social interactions.”
The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods (2010, unknown): “The intercorrelation among these words is low but highly significant (“a” with “an” = .13, “a” with “the” = .09, “an” with “the” = .09), resulting in Cronbach’s a of .14 (for a summary of all reliability statistics, see Pennebaker et al., 2007).”
Automated Crowdturfing Attacks and Defenses in Online Review Systems (2017, methodology): “• LIWC features (62): The Linguistic Inquiry and Word Count (LIWC) software [52] is a widely used text analysis tool in the social sciences.”
Twitter Analysis: Studying US Weekly Trends in Work Stress and Emotion (2016, methodology): “We constructed a stress word count dictionary by following Pennebaker et al. (2007) procedures, with an attempt to derive an alternative stress mea-sure from unobtrusive text analysis that is different from the conventional self-”
What Yelp Fake Review Filter Might Be Doing? (2013, background): “Hence, we can say that LIWC and POS features make little difference compared to word unigram and bigram models.”
Deception detection in Russian texts (2017, background): “LIWC (Pennebaker et al., 2007) is a text analysis program that counts words in psychologically meaningful categories.”