Who You Know in Hollywood: A Network Analysis of Television Writers

Abstract

“It’s who you know, not what you know,” is a familiar phrase—often repeated by professionals in Hollywood. The present study focuses on “who knows who” among Hollywood television writers. Using network analysis, this exploratory study identifies the degree of centralization and types of connections found in this elite writers’ network. Results show a great deal of collaboration in the network, and while male writers are more connected overall in Hollywood, women are more likely to be brokers—a structurally advantageous position. The authors provide explanations for collaboration patterns, especially with regard to gender differences in network roles, and propose avenues for further research.

Notes

^1. “Original run” means the first time a series runs on television; “full run” means the series is over; “partial” run means the series is ongoing.

^2. The spatial placement of the nodes in Figure 1 is based on a spring-embedded layout procedure. The distance between two nodes is determined by a combination of the geodesic distance (i.e., shortest path) between those nodes, node repulsion, and similarity in tie strength. In simpler terms, the procedure treats the links as springs that enact a force upon a given node based on the tie strength between that node and all those to which it is connected. Thus, stronger ties will pull nodes together, while still accounting for the strength of ties to all other nodes.

^3. Network centralization is a measure of the variability or inequality in the degree scores of all nodes in a given network (Monge & Contractor, 2003). It provides a macro-level indicator of the relative heterogeneity of the network, in terms of the linking architecture. Network centralization indicates the extent to which a few nodes exhibit disproportionately high degree scores. A high centralization score represents a high level of inequality in the degree scores, while a low score signifies greater equality. Thus, a high score suggests that a small number of writers are central in the network, with the rest on the periphery. A low centralization score, as was found in this study, suggests a relatively even distribution of degree scores across the entire network.

^4. UCINET offers a core-periphery analysis, which seeks to determine whether the network is a good fit for a core-periphery structure. We ran this on our network, but the network was not a good fit for the strict core-periphery model. This does not mean that there isn’t a core of more densely connected writers (i.e., the central ones); it just means that they are not completely disconnected from the rest of the network.

Additional information

Notes on contributors

Patricia F. Phalen

Patricia F. Phalen (Ph.D., Northwestern University) is an associate professor of Media & Public Affairs at The George Washington University. Her research interests include television production, the work culture of television writers, audience research, and the history of media organizations.

Thomas B. Ksiazek

Thomas B. Ksiazek (Ph.D., Northwestern University) is an assistant professor in the Department of Communication at Villanova University. His research interests include patterns of cross-platform media use, new forms of user engagement with the news, implications of audience behavior for society and the field of journalism, and the application of network analysis to the consumption and production of media.

Jacob B. Garber

Jacob B. Garber (B.A., The George Washington University) is a master’s candidate in English at the University of California, Davis. His research interests include cultural geography, contemporary media consumption, and narratives of the Silicon Valley/Bay Area in television, film and literature.