CoChat
Sign Up
Cited by 476Media Influence and PoliticsSocial Media and PoliticsElectoral Systems and Political Participation

The Hostile Audience: The Effect of Access to Broadband Internet on Partisan Affect

Lelkes, Yphtach, Sood, Gaurav, Iyengar, Shanto·2017·American Journal of Political Science
DOI 10.1111/ajps.12237
Open this paper in CoChat — free account

Abstract

Over the last two decades, as the number of media choices available to consumers has exploded, so too have worries over self‐selection into media audiences. Some fear greater apathy, others heightened polarization. In this article, we shed light on the latter possibility. We identify the impact of access to broadband Internet on affective polarization by exploiting differences in broadband availability brought about by variation in state right‐of‐way regulations (ROW). We merge state‐level regulation data with county‐level broadband penetration data and a large‐N sample of survey data from 2004 to 2008 and find that access to broadband Internet increases partisan hostility. The effect occurs in both years and is stable across levels of political interest. We also find that access to broadband Internet boosts partisans' consumption of partisan media, a likely cause of increased polarization.

Integrity signals

Registry

Crossref · 10.1111/ajps.12237

Cites

80 of 80 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Contemporary media, most notably partisan media and social media, often generate polarized societies due to one-sided information flows.

    “contemporary media, most notably partisan media and social media, often receive condemnation for generating polarized societies due to one-sided information flows”

    From How to study democratic backsliding (2024) · cites this paper as Lelkes et al., 2017

  • Some work suggests clear media effects, including the internet generating affective polarization, Facebook contributing to low trust in institutions, and certain cable news channels (Fox News) leading to an increase in misinformation and issue salience.

    “In terms of acceptance, some work suggests clear media effects.This includes the internet generating affective polarization (Lelkes et al., 2017); Facebook contributing to low trust in institutions (Green et al., 2023; although see Guess et al., 2023a); and certain cable news channels (Fox News) leading to an increase in misinformation (Garrett et al., 2019) and issue salience (Broockman & Kalla,”

    From How to study democratic backsliding (2024) · cites this paper as Lelkes et al., 2017

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Lelkes, Y., Sood, G., & Iyengar, S.
Affiliations
  • University of Amsterdam
  • Independent Researcher
  • Stanford University (US)
ORCID
Venue
American Journal of Political Science
Publisher
Wiley
Published
2015-12-23
Volume
61
Issue
1
Pages
5-20
ISSN
  • 0092-5853 (ISSN-L)
  • 1540-5907
DOI
10.1111/ajps.12237
OpenAlex
W2226773660
Cited by
476
References
80
Citations by year
2026: 38 · 2025: 53 · 2024: 35 · 2023: 35 · 2022: 62 · 2021: 52 · 2020: 97 · 2019: 43 · 2018: 36 · 2017: 16 · 2016: 9
FWCI
67.22
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
American Journal of Political Science (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Media Influence and Politics
  • Social Sciences › Communication › Social Media and Politics
  • Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
Keywords
broadband access, affective polarization, partisan hostility, political interest

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review