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 Gihong Yi 李圻洪 Department of Sociology, Hallym University

Introduction 2 Proportion of Internet Surveys in Surveys of Statistics Korea (%) Year Surveys Mining and Manufacturing Survey Census on Service Industry Cyber Shopping Survey Household Income and Expenditure Survey Food Grain Consumption Survey Populatioan and Housing Census 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)

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 10s through 30s ▫ 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. 3

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 4

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 5

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 6

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

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

I NTENT TO P ARTICIPATE IN I NTERNET S URVEY Men + (vs. Women) Education + Employed + (vs. else) Unmarried + (vs. married) Internet newspaper reading frequency + Non-political donation + Social group participation + Volunteering experience + 9

I NTENT TO P ARTICIPATE IN I NTERNET S URVEY 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. 10

First, just with the demographic variables. Next model includes Internet newspaper reading, donation experience, group participation, and volunteering. 11 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. I SSUES ▫ R EPRESENTATIVENESS ▫ D ISCRIMINATION 12

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. 13