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Paper Number

2148

Paper Type

Short

Description

Many online platforms that thrive on user-generated content (UGC) face the under-provision issue. A new strategy that platforms deploy to tackle this problem is to offer extra content curation tools with lower entry barriers. We study one of such features in online knowledge-sharing platforms: An additional content curation tool that allows users to share free-format content apart from the standard question-and-answer (Q&A) knowledge content. By leveraging a natural experiment occurred in a large Chinese online knowledge-sharing platform, we identify the causal effects of users’ adoption of a new low-barrier content tool on their knowledge contribution in a difference-in-differences (DiD) framework. We find that the adoption of such a low-barrier tool complements knowledge contribution. Specifically, users increased their volumes of answers without compromising effort spent on each answer after adoption. We validate this finding by further addressing the selection bias through a two-step Heckman correction approach with instrumental variable and a look-ahead matching method. Our results bear important implications for platform design and intervention to motivate UGC contribution.

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Dec 12th, 12:00 AM

Complementary or Substitutive? Free-Format Content Production and Knowledge Contribution in Online Knowledge-Sharing Communities

Many online platforms that thrive on user-generated content (UGC) face the under-provision issue. A new strategy that platforms deploy to tackle this problem is to offer extra content curation tools with lower entry barriers. We study one of such features in online knowledge-sharing platforms: An additional content curation tool that allows users to share free-format content apart from the standard question-and-answer (Q&A) knowledge content. By leveraging a natural experiment occurred in a large Chinese online knowledge-sharing platform, we identify the causal effects of users’ adoption of a new low-barrier content tool on their knowledge contribution in a difference-in-differences (DiD) framework. We find that the adoption of such a low-barrier tool complements knowledge contribution. Specifically, users increased their volumes of answers without compromising effort spent on each answer after adoption. We validate this finding by further addressing the selection bias through a two-step Heckman correction approach with instrumental variable and a look-ahead matching method. Our results bear important implications for platform design and intervention to motivate UGC contribution.

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