Converting cultural capital into economic capital: a hybrid newspaper’s content management and performance during economic turbulence

ABSTRACT

A newspaper under siege often struggles to balance its journalistic mission with revenue mission. This study applied Bourdieu’s field theory to the analysis of one American metropolitan newspaper’s content strategies during economic turbulence. The time series analysis of five years of content and finance data showed that the content mix could affect print advertising revenue, but such effects were more indirect, nonlinear, and gradual than those affecting print and online readerships. The interviews with nine executive editors and managers of the newspaper revealed an increasingly collaborative relationship rather than a contested relationship. The newspaper’s managers should differentiate between online and offline content offerings since what appealed to the online readers may not attract local advertisers.

KEYWORDS:

• Cultural capital
• economic capital
• time series analysis
• field theory
• case study
• the editorial–business relationship

Acknowledgements

This research project was supported by the Donald W. Reynolds Journalism Institute.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. This study acknowledges other ways of measuring newspaper content. The normative approach evaluates the content in their perceived social functions in shaping informed citizenry (Porto, 2007; Zaller, 2003) and social influence (Meyer, 2004). The recipient approach measures content by assessing audiences’ knowledge and utility, loyalty, and strength of the relationship with newspapers (Sullivan, 2006). This study, however, departs from a normative approach – the perceived credibility measures, such as accuracy, fairness, and believability (Gladney, Shapiro, & Castaldo, 2007; Payne & Dozier, 2013). Neither does the study evaluate the social influence or political ideology of the newspaper. While those concepts are critical dimensions of journalism, Urban and Schweiger (2014) admitted the difficulties for readers to judge news coverage based on normative quality criteria, such as ethics, objectivity, and comprehensibility. Hence, this study focuses on the objective measures of the objectified cultural capital rather than the subjective perceptions of people.

2. The newsroom archived each story with a unique meta-code to identify the topic of content. The computer programme tracked the meta-code of each story and detected a total of 21 unique meta-codes spanning the five-year period. Meta-codes of relevant topics were then aggregated to a single content category. News content category included two meta-codes: news and local news. Sports content category had only one meta-code named sports. Business and technology category included five meta-codes: motoring, business, job market, and personal technology and home/real estate. Opinion and editorial content category had one meta-code named opinion. Feature category included 12 meta-codes: ticket, food, pacific northwest, travel, northwest weekend, books, entertainment, digs, practical gardening, wine, movie times, and religion.

3. The newsroom provided a list of the counties where they primarily covered and distributed newspapers. Stories about cities in the newspaper’s designated counties were coded as local. Stories about cities outside the designated counties but within the home state were coded as regional. Stories about cities outside the home state but in the United States were coded as national. Stories about cities outside the United States were coded as international.

4. A story whose byline contained the full or partial name of the newspaper was categorised as a staff-written. A story whose byline referred to other news organisations was categorised as a non staff-written.

5. There are three dimensions of content measurements. The topic dimension has five content series; the origin dimension has two content series; and the geographic focus dimension has four content series. In essence, three sets of the content series (IVs) modelled the variances of the four dependent series. A total of 12 multivariate times series analysis were performed.

6. The newsroom archived non-commercial content published in print and online. However, the content analysis of this study did not include blogs, columns, multimedia, slideshows, and event calendars published online.

7. Multivariate times series analysis requires additional steps in diagnosing the best-fitting ARIMA model. Cross-correlation function has to be checked between the dependent series (i.e. revenue series) and the pre-whitened independent series (i.e. content series). A significant CCF statistics at lag X indicates the independent series at time interval X is significantly correlated with the dependent series. This correlation is accounted for by adding numerators terms to the transfer function of the independent series. The numerator orders specify which previous values from the selected independent series are used to predict current values of the dependent series. For example, a numerator order of 1 specifies that the values of independent series from one period in the past and the current period is used to predict the current value of the dependent series.

8. The expert modeller originally generated the best fitting ARIMA model as (0,1,0)(0,0,1)₁₂. However, this model only explained about 34.2% variance, which was much lower than the base model. Hence, the customised ARIMA model (0,1,0)(1,0,0)₁₂ was adopted instead and the results were proven better.

Additional information

Notes on contributors

You Li

You Li (PhD University of Missouri, 2012) is an Assistant Professor of Journalism at Eastern Michigan University and does research in media history, media sociology, and media management. Her research traces the historical and contemporary evolvement of journalism with a particular emphasis towards the relationship between the autonomous and heteronomous forces that shape journalism’s landscape. Her current projects examine how the integration of new editorial and business practices such as the rise of participatory culture and native advertising may have affected journalistic autonomy and further blurred the editorial-business boundary.

Esther Thorson

Esther Thorson is a Professor of Journalism at Michigan State University. She publishes extensively in advertising message effects and the relationships between news consumption and political participation. At MSU Thorson is working on news consumption patterns and fake news and fact-checking efforts; several new political socialisation projects, and how news stories about controversial and politicised subjects (e.g. global warming) can be rewritten in ways that reduce the wholesale rejection of them by those who tend to reject fact-based information when it is inconsistent with their world views.