Construction and Initial Validation of a Dictionary for Global Citizen Linguistic Markers

Construction and Initial Validation of a Dictionary for Global Citizen Linguistic Markers

Stephen Reysen (Texas A&M University Commerce, USA), Lindsey Pierce (Texas A&M University Commerce, USA), Gideon Mazambani (Texas A&M University Commerce, USA), Ida Mohebpour (Texas A&M University Commerce, USA), Curtis Puryear (Texas A&M University Commerce, USA), Jamie S. Snider (Texas A&M University Commerce, USA), Shonda Gibson (Texas A&M University Commerce, USA) and Marion E. Blake (Texas A&M University Kingsville, USA)
DOI: 10.4018/978-1-4666-9461-3.ch041
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Abstract

The four studies constructed and examined the validity of a text-based dictionary for assessing the values related to global citizenship. In Study 1, an initial list of words related to global citizens was obtained by conducting an analysis of participant definitions of the construct. In Study 2, the list obtained in Study 1 was further explored through a reaction time based categorization task. Words most quickly and reliably associated with global citizens were combined with synonyms to comprise the final global citizen dictionary. In Study 3, a greater number of global citizen related words were used to describe a global citizen (vs. entrepreneur). In Study 4, the use of global citizen related words when describing one's core values was shown to predict antecedents, identification, and outcomes of global citizenship. Together, the results provide initial validation of a linguistic measure of values related to global citizenship.
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1. Introduction

The amount of information accessible in the world today is growing exponentially. For example, the number of websites on the Internet expanded from 630 million in 2013 to 861 million in 2014—a 37% growth (Netcraft, 2014). Between 2006 and 2011 the number of self-published books grew by 287% (Flood, 2014). The number of open-access journal articles published grew 24.7% from 2008 (153,814 articles) to 2009 (191,851 articles) (Laakso et al., 2011). Together, these statistics point to an ever-increasing amount of knowledge being produced and disseminated each year. Accordingly, the growing amount of textual information being generated has lead to current interest and examination of content analysis computer programs (Cohen, 2012). Within psychology, the Linguistic Inquiry Word Count (LIWC; see Pennebaker, Chung, Ireland, Gonzales, & Booth, 2007 for a review of the development and psychometric properties of the program) is a favored content analysis program which analyzes an individual's language usage in order to provide meaningful information about the author.

Individuals’ language use reflects a variety of psychological functions such as those related to relationships, cognitive patterns, personality, and beliefs (Tausczik & Pennebaker, 2010). Prior to the emergence of computer programs like the LIWC, exploring the relationship between a person’s language and other psychological phenomena required the use of complex and time consuming methods (e.g., content coding which may lead to subjective interpretations of the text). However, innovations in technology and the development of these programs have led to better techniques for research in this area. The LIWC program has been utilized to examine a variety of topics in the past literature, including emotional expression (Bantum & Owen, 2009), intragroup status (Dino, Reysen, & Branscombe, 2009; Reysen, Lloyd, Katzarska-Miller, Lemker, & Foss, 2010), cognitive rigidity and extremism (Cohen, 2012), mindfulness (Collins et al., 2009), moral values (Graham, Haidt, & Nosek, 2009), beliefs about privacy (Vasalou, Gill, Mazanderani, Papoutsi, & Joinson, 2011), honesty and deception, group processes, relationship stability and satisfaction, and cognitive complexity (for a review see Tauscizk & Pennebaker, 2010).

Text analysis programs, afford researchers various benefits such as allowing them to analyze large samples of text quickly and efficiently (see Pennebaker & Chung, 2013) as well as giving them the ability to examine text from individuals around the world or even from those who have long since been deceased. Examples of these methods include past research by Petrie, Pennebaker, and Sivertsen (2008), which investigated language usage in Beatles songs, and Ireland and Pennebaker's (2010) research on letters which were exchanged between Freud and Jung. Using computer programs to analyze text also aids in avoiding possible social desirability biases associated with self-report data. Furthermore, the LIWC program allows researchers to construct new dictionaries (a collection of words that reflect a particular category). In the present paper we report the construction and initial validation of a dictionary to assess language usage related to global citizenship.

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