IWIS 2012 September 2012 Daejeon Korea Social Participation

IWIS 2012 September 2012 Daejeon, Korea Social Participation and Intent to Participate in Internet Surveys U-Seok Seo 徐佑錫 Department of Urban Sociology, University of Seoul usseo@uos. ac. kr Gihong Yi 李圻洪 Department of Sociology, Hallym University gihongyi@hallym. ac. kr

2 Introduction • Internet Surveys in Korea increased quite consistently ▫ Internet survey: 6. 4% in 2005, 16% in 2011 (KORA) ▫ Marketing analysis using online panels / Web-based social surveys ▫ Government statistics collected through Internet surveys (e. g. , Statistics Korea, formerly the National Statistical Office) Proportion of Internet Surveys in Surveys of Statistics Korea (%) 　 　 　 Surveys 2005 Year 　 　 　 2007 2008 2009 2010 2011 58. 8 52. 6 61. 3 62. 5 63. 9 - 1 13 14. 9 19. 7 Cyber Shopping Survey 27. 9 39. 7 45. 8 49 48. 3 Household Income and Expenditure Survey 38. 6 42. 4 48. 8 46 46. 8 - - 16. 9 24 40. 4 　 　 　 47. 9 　 Mining and Manufacturing Survey Census on Service Industry Food Grain Consumption Survey Populatioan and Housing Census 0. 9

3 Reasons for Increase in Internet Surveys • Increase in Internet use in Korea ▫ The rate of Internet use in Korea: 78. 0% (July in 2011, KISA) ▫ 99% use Internet in the age groups 10 s through 30 s ▫ Age gaps disappearing • Increasing difficulties for traditional surveys ▫ Increase in the refusal rate of face-to-face surveys, due to lifestyle diversification and privacy concerns ▫ The usage of landline phone drops, which leads to difficulties in contacting young people.

4 Internet Surveys as an Alternative Mode of Data Collection • Advantages of Internet Surveys ▫ Data collection with less cost and time ▫ Increasing accessibility with certain groups of population ▫ Enhanced monitoring of the ongoing process of data collection • Sociologists and other academic researchers are reluctant to use online survey data. ▫ Cf. marketing research • Sample representativeness ▫ Mostly non-probability sampling ▫ ‘Volunteers’ or ‘convenience’ sampling

5 Issues regarding Representativeness • Two points ▫ Decreasing coverage error ▫ Self-selection bias remains and gains more importance • Harris Interactive’s prediction on the US 2000 presidential election ▫ Online panelists ▫ Reference survey based on probability sampling towards the same target population ▫ Propensity score adjustment • Propensity Score Adjustment ▫ Many studies since Harris Interactive’s prediction (Schonlau et al. , 2009; Lee & Valliant, 2009; Valliant & Dever, 2011) ▫ Studies in Korea (Kim & Lee, 2003; Lee & Jang, 2009; Huh and Cho, 2010) • Selection of variables ▫ Details about the selection of variables for adjustment purposes often remain undisclosed. ▫ Unfeasible in other research situations ▫ Insufficient theoretical justification and generalization

6 Social Participation and Intent to Participate in Internet Social Survey • “The Societal Trend Toward Self-Administration” (Dillman, 2000) • Strong belief in relationship between public opinion and democracy • Civic duty and survey participation (e. g. , Couper, Singer & Kulka, 1998) • Topic interest and survey participation (Groves, Presser & Dipko, 2004) • The impact of online activities on social/political participation in Korea

7 Social Participation and Social Survey Participation Groves, Singer & Corning (2000) “Leverage-Salience Theory”

8 • Data Social Survey 2009, Statistics Korea (formerly the National Statistical Office, ROK) • Research Q Who shows intent to participate in Internet surveys?

9 INTENT TO PARTICIPATE IN INTERNET SURVEY Men + (vs. Women) Education + Employed + (vs. else) Unmarried + (vs. married) Internet newspaper reading frequency + Non-political donation + Social group participation + Volunteering experience +

10 INTENT TO PARTICIPATE IN INTERNET SURVEY • Those who expressed intent to participate in internet survey are relatively: ▫ Young ▫ Well-educated ▫ Often donate non-politically. ▫ Participate in many social groups. ▫ Volunteer often.

11 Logistic Regression of Intent to Participate in Internet Surveys • First, just with the demographic variables. • Next model includes Internet newspaper reading, donation experience, group participation, and volunteering.

12 Logistic Regression of Intent to Participate in Internet Surveys • Confirms the results of previous descriptive analyses. • LR increases (SS). • Those who express intent to participate in Internet surveys differ (from those who do NOT) ▫ Demographically ; and also ▫ By the degree of social participation. • ISSUES ▫ REPRESENTATIVENESS ▫ DISCRIMINATION

13 Implications for Issues of Internet Surveys • Representativeness ▫ In addition to demographic variables and digital divide, diverse social activities affect the intent. • Potential Discrimination ▫ Socially-inactive groups may be undersampled. ▫ This may potentially lead to discrimination against the less visible groups.