Many studies have successfully analyzed language, including male/female differences, not only at a broader contextual sentence level, but also at the phrase and word level. While a word-based approach can be fraught with problems due to the lack of context and the inability to recognize sarcasm for example (a feat that, even today, can only be accomplished automatically through visual semantics and neural networks (Schifanella, Juan, Tetreault, & Cao, 2016)), a solid strand of research now suggests that we are, in fact, able to glean insights about
individuals’ underlying emotions, thoughts, and motives and their language use in great detail by using a categorized word-counting approach online and elsewhere (see for example the works of Correa, Hinsley, & de Zúñiga, 2010; Golbeck, Robles, Edmondson, et al., 2011; Gottschalk, Stein, & Shapiro, 1997; Iacobelli, Gill, Nowson, & Oberlander, 2011; Mairesse et al., 2007; Misersky et al., 2014; Pennebaker, Booth, et al., 2007; Pennebaker & Francis, 1996; Pennebaker & King, 1999; Pennebaker et al., 2003; Schwartz et al., 2013; Tausczik & Pennebaker, 2010; M. Wolf et al., 2008; Yarkoni, 2010) and that men and women do “adopt different and almost unique gender-based behavioral patterns in communication” (Kokkos & Tzouramanis, 2014, p. 3). Studies looking into specific words/word categories were able to confirm some of the
stereotypes about female language use at the phrase-level such as tentativeness (Newman et al., 2008).
In English, women used more intensive adverbs (e.g very, extremely), more conjunctions (e.g. but), and more modal auxiliaries (could, may, might), which could indicate a question mark in the statement (Biber, Conrad, & Reppen, 1998; McMillan, Clifton, McGrath, & Gale, 1977; Mehl & Pennebaker, 2003; Mulac et al., 2001). Male speech, on the other hand, has been associated with a higher frequency of swear words, longer words (> 6 letters), higher use of articles, and overall more references to location (Mehl & Pennebaker, 2003; Mulac, Lundell, & Bradac, 1986). Koppel, Argamon, and Shimoni (2003) discriminately separated male and female authors in a sample from the British National Corpus (BNC), encompassing fiction and non- fiction; their prediction algorithm achieved roughly 80% accuracy. In a similar vein, Biber et al. (1998) used parts of speech to investigate if a given text sample was more involved (more pronouns, present-tense verbs) or more informative (more nouns, long(er) words). They found that the language of females was more involved compared to the language of males (Newman et al., 2008). Newman et al. (2008) directed their focus to gender differences in language use and the word categories included in the English LIWC dictionary.5 Their findings showed “small but
consistent gender differences in language use” (Newman et al., 2008, p. 229). The women in their study used language more to discuss people, what they were doing, and to communicate internal processes to others (including doubts). Further, the list of words that women use more than men also comprised thoughts, emotions, senses, negations, as well as present and past tense verbs (Newman et al., 2008). Men, on the other hand, used language predominantly to label external events, objects, and processes. They also discussed occupation, money, and sports more
than women. On the word level, they used numbers, articles, prepositions, and long words more in addition to more swear words. Interestingly, Newman et al. (2008) did not find discriminate differences in male and female use of references to sexuality, anger, time, use of first-person plural, overall number of words, and qualifiers (exclusion words such as but, although) looking at an archive of electronic text samples from 70 studies from 22 laboratories in the United States, New Zealand, and England. As mentioned above, further studies in cognitive psychology,
computational linguistics, and computer forensics show that women and men do adopt different, almost unique gender-based behavioral patterns in communication (Kokkos & Tzouramanis, 2014). Kokkos and Tzouramanis (2014) used content-based features and traditional linguistic features to analyze potential gender differences and found that men showed distinct patterns of more marked expressions of independence and hierarchical power while women used more emotional language, intensive adverbs, and affective adjectives (quite, adorable, charming, lovely).
Finally, Schwartz et al. (2013) used Facebook data to investigate topic and word use based on sociological variables, such as age, and gender. They were able to corroborate many previous findings on gender-related word use (also using LIWC): Females used more emotion words in general (e.g. ‘excited’) and first-person singular pronouns (‘I’) as well as making more references to psychological and social processes (e.g. ‘love you’). Males, on the other hand, used more swear words and made more object references (e.g. ‘xbox’). In terms of age, the youngest participants used significantly more slang, emoticons, and Internet speak (e.g. ‘idk,’ ‘lol’). Topics also progressed with age (school-related topics for 13-18-year olds, college-related topics for 19-22-year olds) (Schwartz et al., 2013). However, the emotion-word category has produced contentious findings in research. While Mulac, Studley, and Blau (1990) as well as Thomson and
Muracher (2001) showed that women did use more emotion words, Mulac, Seibold, and Farris (2000) showed the opposite investigating male and female managers in a work environment. In light of these conflicting findings, it seems important to sort out what kind of emotion words were used: Mehl and Pennebaker (2003) suggested that women do use more positive emotion words, while men used more words related to anger distinguishing the kinds of emotion words in question.