Neighborhoods in the Network Society the e-Neighbors study

Abstract

This study examines whether the Internet is increasingly a part of everyday neighborhood interactions, and in what specific contexts Internet use affords the formation of local social ties. Studies of Internet and community have found that information and communication technologies provide new opportunities for social interaction, but that they may also increase privatism by isolating people in their homes. This paper argues that while the Internet may encourage communication across great distances, it may also facilitate interactions near the home. Unlike traditional community networking studies, which focus on bridging the digital divide, this study focuses on bridging the divide between the electronic and parochial realms. Detailed, longitudinal social network surveys were completed with the residents of four contrasting neighborhoods over a period of three years. Three of the four neighborhoods were provided with a neighborhood email discussion list and a neighborhood website. Hierarchical linear modeling (HLM) was used to model over time the number of strong and weak ties, emailed, met in-person, and talked to on the telephone. The neighborhood email lists were also analyzed for content. The results suggest that with experience using the Internet, the size of local social networks and email communication with local networks increases. The addition of a neighborhood email list further increases the number of weak neighborhood ties, but does not increase communication multiplexity. However, neighborhood effects reduce the influence of everyday Internet use, as well as the experimental intervention, in communities that lack the context to support local tie formation.

Keywords:

• Community
• social networks
• weak ties
• computer mediated communication
• political communication
• Internet
• neighborhood effects
• social ecology
• e-government
• local media
• community network
• informatics

Acknowledgements

This work was supported by the National Science Foundation (SES-0219538), the American Sociological Association Fund for the Advancement of the Discipline, the NEC Corporation Fund for Research in Computers and Communications, the MIT Humanities, Arts and Social Sciences Fund, and Microsoft Research. I have also benefited from the support of the Annenberg School for Communication at the University of Pennsylvania, the Department of Urban Studies and Planning at MIT, and the Saguaro Seminar and the Taubman Centre for State and Local Government at the John F. Kennedy School of Government at Harvard University. I am indebted to the following people for their support at various stages of this research: Pablo Boczkowski, Deborah Linebarger, Alexandra Marin, Jacob Faber, Benjamin Forman, Christine Flemming, Ari Goelman, Brenda Hampton, Kevin Harris, Sonya Huang, Sera Hwang, Lilian Linders, Oren Livio, Vicki Nash, Tawanda Sibanda, Tom Sander, Natalia Sizov, Marc Smith, Jan Steyaert, Georgeta Vidican, Barry Wellman and Gretchen Weismann.

Notes

1 A limited number of community networking studies have done empirical evaluations of community relationships, including the Camfield Estates–MIT Creating Community Connections Project (Pinkett & Bryant 2003) and the Blacksburg Electronic Village (Kavanaugh et al. 2005).

2 For an extensive review of local ICT initiatives across informatics, sociology and communications see Gaved & Anderson (2006).

3 There were significant inconsistencies between the lists of residents compiled by the local annual census, the reverse telephone directory and projections based on the US Census. For example, in estimating the population of adults in the apartment building, census tract data from the 2000 US Census estimated that there would be 267 residents 18 years of age and older. However, the 2001 annual census for the City of Boston recorded 356 individuals by name over the age of 18, and the reverse telephone directory listed 188 unique names. When the City of Boston's census was combined with the reverse telephone directory, 442 unique names were produced. In an effort to improve the accuracy of the neighborhood rosters, a letter on university letterhead explaining the study and seeking participants was mailed annually to each person on the neighborhood rosters. Letters that were returned by the post office as ‘undeliverable’ were removed from the neighborhood roster as part of the final analysis.

4 Response rate based on US Census estimates, population counts include all non-institutionalized adults < 18 years of age and all formal dwellings, assume a 5 percent vacancy rate in the apartment building, 3 percent in the gated community and 1 percent in the suburbs.

5 Age was not included as a variable in this analysis because it correlated very strongly with tenancy, with older individuals likely to have lived in a neighborhood longer than younger individuals.

6 Cramer's V confirms that the difference between neighborhoods was statistically significant. While the value of Cramer's V suggests a relatively weak relationship, caution should be taken in interpretation since two categories of the neighborhood variable measure the same construct (a suburban community). When the crosstabs were reanalyzed using one, or combined into a measure of both suburban neighborhoods (not shown), there was a small to moderate increase in both strength and significance of the relationships.

7 No variable was modeled for use of the e-Neighbors website. Not only was use of the website very low, but those who used the site were the most likely to have sent a message to the neighborhood list.

8 Intensity is calculated based on a participant's actual network size (number recognized), not on the potential network available within his/her neighborhood (neighborhood size).