This is the slide presented at the session, "Has public opinion research helped sustain representative democracy in Asia?(2)" in 2014 ANPOR Conference. In this slide, I verified the effects of online election campaign in 2013 Japan upper house election.

1. Did the Online Election Campaign Fail?: a Survey Analysis of the Effects of the Online Campaign in the 2013 Japan Upper House Election
Morihiro OGASAHARA
2014 ANPOR Annual Conference, Niigata, Japan
29, November, 2014

2. Background
•2013 Japan Upper House Election
–The interest was low level
–The first online election campaign in Japan
•Expectations for online election campaign
–increase the political interest of voters
–enhance the importance of political issues
–promote dialogues between candidates and voters

3. Voter turnout
•52.1% (third-lowest since WW2)
Failure of the online election campaign?

4. Research Questions
•How much was the exposure?
–To the online election campaign
•How much was the effect?
–To political interest
–To voting behavior
–To party support change

5. Research Methods
•2-wave panel survey
–1st wave: before the election (6/29 ~ 6/30)
–2nd wave: after the election (7/21 ~ 7/22)
•Sample
–Online survey panel of the research company
–1st : 2,691 respondents
–2nd: 1,523 respondents (56.6% of 1st )

6. Variables
•Dependent variables
–Political interest at 2nd wave
–Voting behavior
–Party support change
•Independent variables
–Political interest at 1st wave
–Exposure to electoral information
–TV, newspaper, conversation, election campaign

7. Exposure rate to traditional sources
•Television was the highest
Offline election campaign
59.0%
(%)

8. Exposure rate to online election campaign
•Rather low as a whole
Online election campaign
18.3%
(%)

9. To political interest
• Positive effect
– Regression model explaining political interest(2nd)
β t
（Intercept) 9.713 ***
Age 0.026 1.426
Sex -0.079 -4.238 ***
Political interest (1st) 0.619 31.219 ***
Television 0.041 1.999 *
Newspaper 0.055 2.559 *
Conversation 0.100 4.530 ***
Offline election campaign 0.029 1.311
Online election campaign 0.041 2.132 *
Adjusted R2 0.537
†：p<0.1, *：p<0.05, **：p<0.01, ***:p<0.001

10. To voting behavior
•Positive effect
–Logistic regression model
†：p<0.1, *：p<0.05, **：p<0.01, ***:p<0.001
BSE（Intercept)-1.8510.371*** Age0.0160.006** Sex-0.2370.133† Political interest (1st)0.5380.062*** Television0.0330.170Newspaper0.3200.152* Conversation0.6620.153*** Offline election campaign0.2000.154Online election campaign0.4200.207* Nagelkelke R20.229

11. B SE
（Intercept) -2.143 0.342 ***
Age 0.007 0.005
Sex 0.015 0.116
Political interest (1st) 0.180 0.056 **
Television 0.621 0.174 ***
Newspaper 0.204 0.129
Conversation 0.190 0.134
Offline election campaign 0.188 0.136
Online election campaign 0.322 0.149 *
Nagelkelke R2 0.093
To party support change
• Positive effect
– Logistic regression model
†：p<0.1, *：p<0.05, **：p<0.01, ***:p<0.001

12. Discussion
•Push or pull
–Push media: passive
–Pull media: active
•One-way or two-way
–One-way: audience
–Two-way: participant
•Short term or long term
–Short term: election
–Long term: engagement

13. Conclusion
•The online election campaign succeeded in fact
–Statistically significant positive effects
–More effective than traditional sources
•Online election campaign should be conducted in suitable ways
–Integrate online and offline
–Build relationships
–Connect with voter’s social network, COI

14. Thank you for your attention! E-mai: m36oga@kansai-u.ac.jp