Conceptualizing Communication Capital for a Changing Environment

Abstract

With rapidly evolving technologies, boundaries between traditional modes of communication have blurred, creating an environment that scholars still describe from viewpoints as researchers in interpersonal, organizational or mass communication. This manuscript looks at the social capital literature and argues for conceptualizing “communication capital” to help understand the impact of communication phenomena in a changing environment. The literature has treated interpersonal communication variables as components of social capital and mass communication variables as factors affecting social capital, but scholars long ago recognized their reinforcing nature, leading us to develop a concept of communication capital merging symbolic activity across domains in its potential for impacting civic engagement, defined as persistent communication patterns that facilitate social problem solving in the community. Analysis of survey data shows that 4 dimensions of communication capital explain variance in civic engagement beyond that accounted for by traditional measures of social capital, media use, neighborhood communication, and efficacy.

Keywords:

• Civic Engagement
• Communication Capital
• Communication Theory
• Political Communication
• Social Capital

Notes

Note. The top value in each cell is the bivariate correlation; while the second is a partial correlation controlling for age, education, household income, gender and ethnicity.

*p < .05. **p < .01. ***p < .001.

^a R = .47, R ² = .22; F(12, 254) = 5.87, p < .001.

^b R = .56, R ² = .31; F(12, 254) = 9.50, p < .001.

^c R = .54, R ² = .30; F(12, 254) = 8.90, p < .001.

^d R = .65, R ² = .43; F(12, 254) = 15.80, p < .001.

Certainly, other aspects from a variety of disciplines have been brought into the discussion of social capital, including culture and the arts (Dubinsky, 2006; Jeannotte, 2006), personality (Scheufele & Shah, 2000), access to expertise (Frank, Zhao, & Borman, 2004), community organizing (Gittell & Vidal, 1998; Greeley, 1997; Henderson, Taylor, & Thomson, 2002), economic development (Mencken, Bader, & Polson, 2006), ethnic groups (Steury, Spencer, & Parkinson, 2004), and the importance of social capital for society (Gozzi, 2003–2004).

Putnam (1995) identified social capital as “features of social organization such as networks, norms, and social trust that facilitate coordination and cooperation for mutual benefit” (p. 67). Thus, the focus is on collective action and consequences for the whole, not the individual. We are not saying that application of the concept within organizations of personal contexts are not useful or legitimate efforts to extend the concept and built theory, but we narrow the focus to concentrate on communication.

Alpha measures the extent to which all items measure the same thing, but our scale is more like a summary index, measuring the build up of such discussion, rather than the extent to which it occurs across all contexts. Thus, the somewhat low level is reasonable.

Age was coded into the following categories: 1 = 18–20, 2 = 21–30, 3 = 31–40, 4 = 41–50, 5 = 51–60, 6 = 61–70, and 7 = 71 or older (M = 4.39, S = 1.70, n = 244). Ethnic/racial background was coded into the following categories: Black or African American, White or Caucasian, Hispanic, Asian, American Indian, “mixed,” and “other.” Formal education was coded into the following categories: 1 = completed grade school (8 years or less), 2 = some high school, 3 = high school graduate, 4 = some college, 5 = college graduate, and 6 = advanced college degree (M = 4.27, S = 1.12, n = 246). Annual household income was coded into the following categories: $10,000 or less; $10,001 to $20,000; $20,001 to $30,000; $30,001 to $40,000; $40,001 to $50,000; $50,001 to $75,000; $75,001 to $100,000; $100,001 to $150,000; and more than $150,000 (M = 4.86, S = 2.14, n = 212).

The organizational membership index is positively related to three of the four measures of political involvement (political activities, r = .38, p < .001; perceived personal leadership, r = .27, p < .001; and perceived personal involvement, r = .28, p < .001), the metro quality of life measure is related to two (perceived personal leadership, r = .18, p < .002; perceived personal political involvement, r = .12, p < .03), and community attachment is correlated with three of the four measures of political involvement (political activities, r = .19, p < .001; perceived personal leadership, r = .20, p < .001; and perceived personal involvement, r = .28, p < .001). The item measuring trust in neighbors is correlated with all three: political activities (r = .11, p < .05), perceived personal leadership (r = .26, p < .001), and perceived personal involvement (r = .18, p < .002).

Political efficacy is related to all measures of political involvement (political activities, r = .24, p < .001; perceived personal leadership, r = .39, p < .001; and perceived personal involvement, r = .28, p < .001). The strength of one's neighborhood communication is correlated with two measures of political involvement (perceived personal leadership, r = .29, p < .001; and perceived personal involvement, r = .28, p < .001). Several of the media use variables are related to political involvement. Those who go on the Internet more often engage in more political activities (r = .12, p < .04) and do not think that government bodies collaborate to solve problems (r = −.12, p < .04). Watching the news on television more frequently is related to perceived personal leadership (r = .11, p < .05) and perceived personal involvement (r = .11, p < .05), and the correlation with engaging in political activities approaches statistical significance (r = .10, p < .06). Listening to the radio is not related to any political involvement measures, but reading the newspaper more frequently is correlated with all three of them (political activities, r = .22, p < .001; perceived personal leadership, r = .25, p < .001; and perceived personal involvement, r = .27, p < .001). The more magazines one reads, the higher one's perceived personal leadership (r = .27, p < .001) and perceived personal involvement (r = .21, p < .001).

Political efficacy is related to all four measures of social capital (organizational membership index, r = .13, p < .02; perceived metro quality of life, r = .13, p < .02; community attachment, r = .16, p < .01; and trust in neighbors, r = .15, p < .01).

Involvement in the neighborhood communication network is correlated with three of the four social capital measures (organizational membership, r = .10, p < .05; trust in neighbors, r = .30, p < .001; and community attachment, r = .23, p < .001).

Those who go on the Internet more frequently are higher on all social capital measures. Correlations with the former are organizational membership (r = .11, p < .05), metro quality of life (r = .13, p < .05), trust in neighbors (r = .20, p < .001), and community attachment (r = .15, p < .01). Time spent watching television is related to only one social capital measure, and that is a negative correlation with organizational membership (r = −.14, p < .02) Watching television news more often is related to only one social capital measure, trust in neighbors (r = .15, p < .02). Time spent listening to the radio is negatively related to perceived metro quality of life (r = −.12, p < .03). Reading the newspaper more frequently is correlated with three of the four social capital measures (organizational membership, r = .21, p < .001; trust in neighbors, r = .12, p < .03; and community attachment, r = .13, p < .02).

Additional information

Notes on contributors

Leo Wayne Jeffres

Leo Wayne Jeffres (Ph.D., University of Minnesota, 1976) is a professor in the School of Communication at Cleveland State University.

Guowei Jian

Guowei Jian (Ph.D., University of Colorado, 2003) is an associate professor in the School of Communication at Cleveland State University.

Sukki Yoon

Sukki Yoon (Ph.D., University of Illinois, 2005) is a professor in the Marketing Department at Bryant University.