Plugged In: Predicting Podcast Audiences
and their Political Participation
Monica Chadha
Alex Avila
Homero Gil de Zuniga
School of Journalism
University of Texas – Austin

Introduction and Rationale
Researchers know little about who podcast
audiences are.
The technology is being adopted rapidly.
Little is known about the secondary effects of
this technology- namely political participation.

Podcast- operationalized
“A digital audio or video file that is
episodic; downloadable; program-driven,
mainly with a host and/or theme; and
conveniently accessible, usually via an
automated feed -- such as Really Simple
Syndication (RSS) feed -- with computer
software.”

RQ and Hypotheses
RQ: Who is downloading podcasts? What is a
typical demographic snapshot of a podcast
listener and do demographic variables predict
podcast use?
H1: Podcast use for news will predict political
participation online.
H2: Podcast use for news will predict political
participation offline.

Methodology
Sample data provided by the Media Research
Lab at the University of Texas at Austin.
Information was collected via a web-based
survey between Dec 15, ‘08 and Jan 5, ‘09.
Sample was matched with the important
demographic variables of the U.S. National
Census, specifically gender and age.
1,482 valid cases; response rate was 17.3
percent.
 Final sample = 958 participants

Findings: T1- Demographics
Users
N=115 Podcast type
Politics
N=39
Sports
N=17
Entertainment
N=59
News
N=40
Education
N=39
Other
N=42
Gender
Female
Male
57.4
42.6
56.4
43.6
64.7
35.3
55.9
44.1
65.0
35.0
56.4
43.6
64.3
35.7
Race
White
Non-White
72.2
27.8
66.7
33.3
82.4
17.6
72.9
27.1
70.0
30.0
69.2
30.8
73.8
26.2
Income
Bel 39,999
40–69,999
70-109,999
110,000 up
20.8
25.1
36.4
17.4
25.7
20.5
36.0
18.0
29.4
17.7
23.5
29.4
17.0
23.8
40.8
18.7
25.0
20.0
40.0
15.0
23.1
28.3
28.3
20.5
21.4
38.1
31.0
9.5

T2- Demographic Regression
B s.e. Wald Exp (B)
Demographics
Gender (Female) -.424* .209 4.131 .65
Race (White) -.794*** .236 11.350 .45
Age -.046 .030 2.289 .96
Education .124# .072 3.016 1.13
Income .058* .027 4.699 1.06
Nagelkerke’s R
Square
.072***
Cell entries are B coefficients (unstandardized), standard error, Wald χ2
and odds ratio.
N=958
* p < .05, ** p < .01, *** p < .001

T3 – Online/Offline Part.
Online Political
Participation
Offline Political Participation
Demographics
Age
Education
Gender (Female)
Income
Ethnicity
R Square
.031
.139***
.027
- .088**
.027
2.9%***
.064*
.277***
.050#
.069*
.059#
12.3%***
Media use & Partisanship
Media Use
Partisanship
R Square change
.297***
.121***
11.9%***
.189***
.066*
4.6%***
Podcast Use
Podcast Use
R Square change
.164***
2.6%***
.105**
1.1%**
TOTAL R SQUARE 17.4%*** 18%***
N=958. Cell entries are standardized Beta coefficients. # p < .10, * p < .05, ** p < .01, *** p < .001

Conclusions
Males tend to use podcasts more than
females. Also, higher income bracket =
increased likelihood of using podcasts.
Minorities seem to use this technology to a
larger degree than White individuals.
Entertainment seems to be the most popular
genre for podcast users.
Established an empirical relationship between
podcast use and political participation, online
and offline.

Conclusions
Males tend to use podcasts more than
females. Also, higher income bracket =
increased likelihood of using podcasts.
Minorities seem to use this technology to a
larger degree than White individuals.
Entertainment seems to be the most popular
genre for podcast users.
Established an empirical relationship between
podcast use and political participation, online
and offline.