Content Reuse and Interest Sharing in Tagging Communities

Tagging communities represent a subclass of a broader class of user-generated content-sharing online communities. In such communities users introduce and tag content for later use. Although recent studies advocate and attempt to harness social knowledge in this context by exploiting collaboration among users, little research has been done to quantify the current level of user collaboration in these communities. This paper introduces two metrics to quantify the level of collaboration: content reuse and shared interest. Using these two metrics, this paper shows that the current level of collaboration in CiteULike and Connotea is consistently low, which significantly limits the potential of harnessing the social knowledge in communities. This study also discusses implications of these findings in the context of recommendation and reputation systems.Comment: 6 pages, 6 figures, AAAI Spring Symposium on Social Information Processin

Which projects are selected for an innovation subsidy? The Portuguese case

Several empirical studies have analyzed which firm characteristics influence government evaluators in the decision to select specific firms to participate in Research and Develop- ment and Innovation subsidy programs. However, few authors have provided a precise analysis about the selection process of applications submitted for public support. The aim of the present article is to assess differences in investment project characteristics (expected impact) between firms with approved and non-approved applications and to understand which kinds of projects are selected for a subsidy. The analysis is focused on the case study of applications submitted to the Portuguese Innovation Incentive System (SI Innovation) between 2007 and 2013. The impact variables under study are those used in the selection procedure to grant the firm a subsidy, namely the expected impact on exports, value creation, productivity, patent application and qualified employment. Using a counterfactual analysis and Propensity Score Matching estimators, the results show that firms with approved applications are those that expect to invest more and forecast a higher increase in exports and productivity as the result of the investment project. However, these firms in comparison with the control group (those with non-approved applications) have investment projects with a lower contribution to growth and lower economic efficiency (return on investment in terms of productivity). The conclusions of this study could be useful for policy-makers since it provides evidence about firms’ strategic choice concerning investment projects submitted for an Innovation subsidy.info:eu-repo/semantics/publishedVersio