The LIWC2007 Application

James W. Pennebaker, Cindy K. Chung, Molly Ireland,
Amy Gonzales, and Roger J. Booth

Development and Psychometric Properties of LIWC

The ways that individuals talk and write provide windows into their emotional and cognitive worlds. Over the last four decades, researchers have provided evidence to suggest that people’s physical and mental health are correlated with the words they use (Gottschalk & Glaser, 1969; Rosenberg & Tucker, 1978; Stiles, 1992). More recently, a large number of studies have found that having individuals write or talk about deeply emotional experiences is associated with improvements in mental and physical health (e.g., Fratteroli, 2007; Lepore & Smyth, 2002; Pennebaker, 1997). Text analyses based on these studies indicate that those individuals who benefit the most from writing tend to use relatively high rates of positive emotion words, a moderate number of negative emotion words, and an increasing number of cognitive words, and switch their use of pronouns from writing session to writing session (e.g., Campbell & Pennebaker, 2002; Pennebaker, Mayne, & Francis, 1997).

In order to provide an efficient and effective method for studying the various emotional, cognitive, and structural components present in individuals’ verbal and written speech samples, we originally developed a text analysis application called Linguistic Inquiry and Word Count, or LIWC. The first LIWC application was developed as part of an exploratory study of language and disclosure (Francis, 1993; Pennebaker, 1993). The second version, LIWC2001, updated the original application with an expanded dictionary and a more modern software design (Pennebaker, Francis, & Booth, 2001). The most recent evolution, LIWC2007, has significantly altered both the dictionary and the software options. As with previous versions, however, the program is designed to analyze individual or multiple language files quickly and efficiently. At the same time, the program attempts to be transparent and flexible in its operation, allowing the user to explore word use in multiple ways.

The LIWC Framework

The LIWC2007 application relies on an internal default dictionary that defines which words should be counted in the target text files. Note that the LIWC2007.EXE file is an executable file and cannot be read or opened. To avoid confusion in the subsequent discussion, text words that are read and analyzed by LIWC2007 are referred to as target words. Words in the LIWC2007 dictionary file will be referred to as dictionary words. Groups of dictionary words that tap a particular domain (e.g., negative emotion words) are variously referred to as subdictionaries or word categories.

The LIWC Main Text Processing Module

LIWC2007 is designed to accept written or transcribed verbal text which has been stored as a digital file in one of multiple formats, including raw text, ASCII, unicode, or standard files from Microsoft’s Word files. LIWC2007 accesses a single file or group of files and analyses each sequentially, writing the output to a single file. Processing time for a page of single-spaced text is typically a fraction of a second on both PC and Mac computers. LIWC2007 reads each designated text file, one target word at a time. As each target word is processed, the dictionary file is searched, looking for a dictionary match with the current target word. If the target word matches the dictionary word, the appropriate word category scale (or scales) for that word is incremented. As the target text file is being processed, counts for various structural composition elements (e.g., word count and sentence punctuation) are also incremented.

With each text file, approximately 80 output variables are written as one line of data to a designated output file. This data record includes the file name, 4 general descriptor categories (total word count, words per sentence, percentage of words captured by the dictionary, and percent of words longer than six letters), 22 standard linguistic dimensions (e.g., percentage of words in the text that are pronouns, articles, auxiliary verbs, etc.), 32 word categories tapping psychological constructs (e.g., affect, cognition, biological processes), 7 personal concern categories (e.g., work, home, leisure activities), 3 paralinguistic dimensions (assents, fillers, nonfluencies), and 12 punctuation categories (periods, commas, etc). A complete list of the standard LIWC2007 scales is included in Table 1.

The Default LIWC Dictionary

The LIWC2007 Dictionary is the heart of the text analysis strategy. The default LIWC2007 Dictionary is composed of almost 4,500 words and word stems. Each word or word stem defines one or more word categories or subdictionaries. For example, the word cried is part of five word categories: sadness, negative emotion, overall affect, verb, and past tense verb. Hence, if it is found in the target text, each of these five subdictionary scale scores will be incremented. As in this example, many of the LIWC2007 categories are arranged hierarchically. All anger words, by definition, will be categorized as negative emotion and overall emotion words. Note too that word stems can be captured by the LIWC2007 system. For example, the LIWC2007 Dictionary includes the stem hungr* which allows for any target word that matches the first five letters to be counted as an ingestion word (including hungry, hungrier, hungriest). The asterisk, then, denotes the acceptance of all letters, hyphens, or numbers following its appearance.

Each of the default LIWC2007 categories is composed of a list of dictionary words that define that scale. Table 1 provides a comprehensive list of the default LIWC2007 dictionary categories, scales, sample scale words, and relevant scale word counts.

LIWC Dictionary Development

The selection of words defining the LIWC2007 categories involved multiple steps over several years. The initial idea was to identify a group of words that tapped basic emotional and cognitive dimensions often studied in social, health, and personality psychology. With time, the domain of word categories expanded considerably.

Step 1. Word Collection. In the design and development of the LIWC category scales, sets of words were first generated for each category scale. Within the Psychological Processes category, for example, the emotion or affective subdictionaries were based on words from several sources. We drew on common emotion rating scales, such as the PANAS (Watson, Clark, & Tellegen, 1988), Roget’s Thesaurus, and standard English dictionaries. Following the creation of preliminary category word lists, brain-storming sessions among 3-6 judges were held in which words relevant to the various scales were generated and added to the initial scale lists. Similar schemes were used for the other subjective dictionary categories.

Step 2. Judges’ Rating Phases. Once the broad word lists were amassed, words in the Psychological Processes and Personal Concerns and most in the Relativity (excluding verb tense) categories were then rated by three independent judges. In the development of the first LIWC program, the judges were instructed to focus on both the inclusion and exclusion of words in each LIWC dictionary scale list. In the first rating phase, the judges indicated whether each word in the category list should or should not be included on the particular category in question. They were also instructed to include additional words they felt should be included in the category. All category word lists were updated by the following set of rules: 1) a word remained in the category list if two out of three judges agreed it should be included, 2) a word was deleted from the category list if at least two of the three judges agreed it should be excluded, and 3) a word was added to the category list if two out of three judges agreed it should be included. Due to the objective nature of elements in the Standard Language Dimensions category (e.g., articles, pronouns, prepositions), judges’ ratings were not collected for the various lists in that category.

The second rating phase involved the discrimination of LIWC category word elements. Judges were given category level alphabetized word lists (e.g., all Cognitive Process words) and asked to indicate whether each word in the list should or should not be included in the high-level category in question. Judges were then instructed to indicate in which, if any, of the mid-level scale lists the word should be included (e.g., Insight, Causation). All category scale word lists were updated by the following rules: 1) a word remained on the scale list if two out of three judges agreed it should be included and 2) a word was deleted from the scale list if at least two of the three judges agreed it should be excluded. The final percentages of judges’ agreement for this second rating phase ranged from 93% agreement for Insight to 100% agreement for Ingestion, Death, Religion, Friends, Relatives, and Humans.

Step 3. Psychometric Evalutation. The initial LIWC judging took place in 1992-1994. A significant LIWC revision was undertaken in 1997 to streamline the original program and dictionaries. Text files from several dozen studies, totaling over 8 million words were analyzed using the 1997 version of LIWC as well as WordSmith, a powerful word count program used in discourse analysis. Original LIWC categories that were used at very low rates (less than 0.3 percent of words made up the category) or that suffered from consistently poor reliability or validity were omitted. Several new categories, including social processes, several personal concern categories, and the relativity dimensions, were added following the same stringent judge-based procedures described above (including both passes). Finally, once the entire new LIWC dictionary was assembled, any words that were not used at least 0.005 percent of the time in our previous text files or were not listed in Francis and Kucera’s (1982) Frequency Analysis of English Usage were excluded.

Step 4. Updates and Expansions. The most recent version, LIWC2007, involved substantial updating of the dictionaries and modification in the dictionary structure. Drawing on over several hundred thousand text files made up of several hundred million words from both written and spoken language samples, we sought to identify common words and word categories not captured in the earlier LIWC versions. Examining the 2000 most frequently used words, a group of four judges individually and collectively agreed which new words and new word categories were appropriate for inclusion. Based on recent studies suggesting that function words are particularly relevant to psychological processes, we added the categories of Conjunctions, Adverbs, Quantifiers, Auxiliary Verbs, Commonly-used Verbs, Impersonal Pronouns, Total Function Words, and Total Relativity Words. In addition, third person pronouns were divided into 3 rd person singular and 3 rd person plural. Finally, a large group of punctuation marks have been added as separate categories.

For those who are familiar with LIWC2001, it will be clear that some of the original categories have been removed – primarily because these categories had consistently low base rates and were rarely used: Optimism, Positive Feelings, Communication Verbs, Other References, Metaphysical, Sleeping, Grooming, School, Sports, Television, Up, and Down. The category of Unique Words (also known as Type/Token ratio) has also been removed. This category typically correlates with word count at -.80. Note that an alternative default LIWC2001 dictionary is available.

LIWC's Internal Reliability and External Validity

Assessing the reliability and validity of text analysis programs is a tricky business. On the surface, one would think that you could determine the internal reliability of a LIWC scale the same way it is done with a questionnaire. With a questionnaire that taps anger or aggression, for example, participants complete a self-report asking a number of questions about their feelings or behaviors related to anger. Reliability coefficients are computed by correlating people’s answers to the various questions. The more highly they correlate, the reasoning goes, the more the questions all measure the same thing. Voila! The scale is deemed internally consistent.

A similar strategy can be used with words. The LIWC Anger scale, for example, is made up of 184 anger-related words. In theory, the more people use one type of anger word in a given text, the more likely they should be to use other anger words in the same text. To test this idea, we can determine the degree to which people use each of the 184 anger words across a select group of text files and then calculate the intercorrelations of the word use. Indeed, in Table 1, we include these internal reliability statistics, including those of Anger where the alpha reliability ranges between .92 (binary method) and .55 (uncorrected) depending on how it is computed. The internal reliability statistics are based on the correlation between the occurrence of each word in a category with the sum of the other words in the same category. The binary method converts the usage of each of the single words within a given text into either a 0 (not used) or a 1 (used one or more times). The uncorrected method is based on the percentage of total words that each of the category words are used. The binary method has the potential to overestimate reliability based on the length of texts; the uncorrected method tends to underestimate reliability based on the highly variable base rates of word usage within any given category.

But be warned: the psychometrics of natural language use are not as pretty as with questionnaires. The reason is obvious once you think about it. Once you say something, you generally don’t need to say it again in the same paragraph or essay. The nature of discourse, then, is we usually say something and then move on to the next topic. Saying the same thing over and over again is generally bad form.

Issues of validity are also a bit tricky. We can have people complete a questionnaire that assesses their general moods and then have them write an essay which we then subject to the LIWC program. We can also have judges evaluate the essay for its emotional content. In other words, we can get self-reported, judged, and LIWC numbers that all reflect a participant’s anger.

One of the first tests of the validity of the LIWC scales was undertaken by Pennebaker and Francis (1996) as part of an experiment in which first year college students wrote about the experience of coming to college. During the writing phase of the study, 72 Introductory Psychology students met as a group on three consecutive days to write on their assigned topics. Participants in the experimental condition (n = 35) were instructed to write about their deepest thoughts and feelings concerning the experience of coming to college. Those in the control condition (n = 37) were asked to describe any particular object or event of their choosing in an unemotional way. After the writing phase of the study was completed, four judges rated the participants’ essays on various emotional, cognitive, content, and composition dimensions designed to correspond to selected LIWC Dictionary scales.

Using LIWC output and judges’ ratings, Pearson correlational analyses were performed to test LIWC’s external validity. Results, presented in Table 1, reveal that the LIWC scales and judges’ ratings are highly correlated. These findings suggest that LIWC successfully measures positive and negative emotions, a number of cognitive strategies, several types of thematic content, and various language composition elements. The level of agreement between judges’ ratings and LIWC’s objective word count strategy provides support for LIWC’s external validity.

Base Rates of Word Usage

In evaluating any text analysis program, it is helpful to get a sense of the degree to which language varies across settings. Since 1986, we have been collecting text samples from a variety of studies – both from our own lab as well as from 28 others in the United States, Canada, and New Zealand. For purposes of comparison, six classes of text from 72 separate studies were analyzed and compared. As can be seen in Table 2, these analyses reflect the utterances of over 24,000 writers or speakers totaling over 168 million words. Overall, 29 samples are based on experiments were people were randomly assigned to write either about deeply emotional topics (emotional writing) or about relatively trivial topics such as plans for the day (control writing). Individuals from all walks of life – ranging from college students to psychiatric prisoners to elderly and even elementary-aged individuals – are represented in these studies. A third class of text was based on 113 highly technical articles in the journal Science published in 1997 or 2007. A fourth sample included 714,000 internet web logs, or blogs, from approximately 20,000 individuals who posted either on Blog.com in 2004 or LiveJournal.com in the summer and fall of 2001. The fifth sample was based 209 novels published in English between 1700 and 2004. The American and British novels included best-selling popular books as well as more classic novels. Finally, we analyzed data from seven observational studies in which participants were tape-recorded while engaging in conversations with others. The speech samples ranged from transcripts of people wearing audio recorders over days or weeks, strangers interacting in a waiting room, to couples talking about problems, to open-air tape recordings of people in public spaces.

Note: Emotional writing studies require participants to write about their emotions and thoughts about personally relevant topics; Control Writing involves writing about non-emotional topics, such as plans for the day or descriptions of ordinary objects or events; Science articles are published articles in the journal Science in 1997 and 2007. Blogs are from LiveJournal.com which were written in summer and fall, 2001 and from Blogs.com that were downloaded in summer, 2004. Novels refers to either portions or complete works of American and British fiction published between 1800 and 2005; Talking files come from transcripts collected from individuals who are talking in real world unstructured settings.

As can be seen in Table 3, the LIWC2007 version captures, on average, over 86 percent of the words people use in writing and speech. Note that except for total word count and words per sentence, all means in Table 3 are expressed as percentage of total word use in any given speech/text sample. Simple one-way ANOVAs indicated that word usage was significantly different across the four settings for all of the word categories.

In many ways, Table 3 points to the important role that context plays in people’s use of language. Not surprisingly, the topics of writing – as reflected in the current concerns category – vary substantially as a function of genre. More striking, however, are the large differences in people’s use of function words as well as punctuation from genre to genre (cf., Biber, 1988).

Comparing LIWC2007 with LIWC2001

For users of LIWC2001, a new edition of LIWC that uses a different dictionary can be an unsettling experience. Many of the older dictionaries have been slightly changed, a few have been substantially updated (e.g., exclusive words, cognitive mechanisms), and others have been removed or added. To help older users, we include Table 4 which lists the means, standard deviations, and correlations between the two dictionary versions. These analyses are based on a comparison of over 2800 randomly selected texts from each of the genres listed in Tables 3 and 4.

LIWC Dictionary Translations

The LIWC dictionaries have been translated into several languages, including Spanish, German, Dutch, Norwegian, Italian, Portuguese. Several other language translations are underway, including Arabic, Korean, Turkish, and Chinese. To date, these translations have relied on the LIWC2001 dictionary rather than LIWC2007.

LIWC2007 comes with the Spanish and German translations. All others must be received from the original authors (contact Pennebaker@mail.utexas.edu for more information). The Spanish translation (Ramirez-Esparza, Pennebaker, Garcia, & Suria, 2007) was overseen by a native speaker of Mexican Spanish with close help by a Columbian Spanish speaker. The final version involved the collaboration of a native Spanish speaker from Spain. The German LIWC version ( Wolf, Horn, Mehl, Pennebaker, & Kordy, 2008) was developed by all native speaking Germans using high German rather than local dialects.

Additional languages will be added to the LIWC dictionary options as they become available.

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Acknowledgements

Portions of the research reported in this manual were made possible by grants from the National Institutes of Health (MH52391). We are deeply indebted to a number of people who helped with different phases of this project: Laura King, Cheryl Hughes, Becky Smith, Kathy Davison, Janie Keller, Mary Sue Hayward, Brooke Novales, Anne Vano, Michael Crow, Sally Dickerson, and Bernard Rimé.