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Social Ties and User Generated Content: Evidence from an Online Social Network

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Abstract

We use variation in wind speeds at surfing locations in Switzerland as exogenous shifters of users' propensity to post content about their surfing activity onto an online social network. We exploit this variation to test whether users' social ties on the network have a causal effect on their content generation, and whether content generation in turn has a similar causal effect on the users' ability to form social ties. Economically significant causal effects of this kind can produce positive feedback that generate multiplier effects to interventions that subsidize tie formation. We argue these interventions can therefore be the basis of a strategy by the firm to indirectly facilitate content generation on the site. The exogenous variation provided by wind speeds enable us to measure this feedback empirically and to assess the return on investment from such policies. We use a detailed dataset from an online social network that comprises the complete details of social tie formation and content generation on the site. The richness of he data enable us to control for several spurious confounds that have typically plagued empirical analysis of social interactions. Our results show evidence for significant positive feedback in user generated content. We discuss the implications of the estimates for the management of the content and the growth of the network.

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  • Reto Hoffstetter & Harikesh Nair & Scott Shriver & Klaus Miller, 2009. "Social Ties and User Generated Content: Evidence from an Online Social Network," Working Papers 09-28, NET Institute, revised Nov 2009.
  • Handle: RePEc:net:wpaper:0928
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    More about this item

    Keywords

    social networks; user generated content; social interactions; advertising revenue; simultaneity; identification;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • L68 - Industrial Organization - - Industry Studies: Manufacturing - - - Appliances; Furniture; Other Consumer Durables
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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