Probabilistic Personalized Recommendation Models For Heterogeneous Social Data

Content recommendation has risen to a new dimension with the advent of platforms like Twitter, Facebook, FriendFeed, Dailybooth, and Instagram. Although this uproar of data has provided us with a goldmine of real-world information, the problem of information overload has become a major barrier in developing predictive models. Therefore, the objective of this The- sis is to propose various recommendation, prediction and information retrieval models that are capable of leveraging such vast heterogeneous content. More specifically, this Thesis focuses on proposing models based on probabilistic generative frameworks for the following tasks: (a) recommending backers and projects in Kickstarter crowdfunding domain and (b) point of interest recommendation in Foursquare. Through comprehensive set of experiments over a variety of datasets, we show that our models are capable of providing practically useful results for recommendation and information retrieval tasks

Religious Prosocial Crowdlending - Dual-market Success Mechanisms

Paper I is excluded from the dissertation due to copyright. Paper II and III are excluded from the dissertation until it is publishedCrowdfunding is a relatively new and rapidly growing global phenomenon that has appealed to academic curiosity. At its crux, it is rooted in the communal philosophy of greater good. The online technological intervention can be traced back to 2006, while the phenomenon took center-stage in the midst of the 2008 Global Financial Crisis. Over a decade and a half, the crowdfunding industry has grown into several distinct forms and business models. This dissertation started with a systematic literature review that broadly considered four mainstream business models of crowdfunding, and how it is possible to bridge the knowledge gaps left behind. This led to two empirical papers, motivated by the World Bank’s recommendation of a hybrid type of crowdfunding called prosocial crowdlending, to alleviate poverty from the developing economies, where poverty alleviation is the first of the United Nations’ 17 Sustainable Development Goals. While considering the developing economies that are innately non-secular, Islam was one of the religions that did not contribute to economic success as per the extant literature. On the contrary, such Islamic developing economies have thriving religious markets. This presented a dichotomy between theory and practice and a research gap that needed to be addressed. Insights from Max Weber that religions such as Christianity have clearly contributed to economic development of the West were recalled. These insights were applied in the empirical papers focusing on Islam, extending Weber’s seminal work from west to east. The findings of the empirical papers suggest that Islam does contribute to economic growth, albeit in a welfarist sense rather than in a capitalist sense. The overall contribution that this dissertation makes to the religious prosocial crowdlending is in identifying its dual-market success mechanisms through the developed theories and integrated typologies. These explain how religious capital is being converted to economic capital facilitated by trust in otherwise low-trust developing economies, on the supply side, and religious rationality that encourages sustainable micro-entrepreneurship despite the longstanding duality between religion and reason, on the demand side. In doing so, this dissertation also explains how Islam contributes to the economic welfare of such economies, and how to channelize religious capital towards economic development by utilizing technologically enabled religious prosocial crowdlending as a strategic philanthropic tool, to successfully impact poverty by enabling micro-entrepreneurship.publishedVersio

Are All Spillovers Created Equal? The Impact of Blockbusters and the Composition of Backers in Online Crowdfunding

Crowdfunding has emerged alongside the IT development. It is believed that overwhelmingly successful projects, blockbusters, would have significant impacts on the overall crowdfunding platform. However, there are notable limitations in previous studies. First, we consider how the advent of blockbusters impact according to the projects’ similarity with inside and outside clusters, rather than pre-determined category. Second, we examine the blockbusters’ heterogeneity with the type of backers that bring different effects. We use project-level dataset and apply novel clustering method to analyze blockbuster effects. We find empirical evidence that blockbusters have a spillover effect on same categories, especially inside clusters experience larger effects than outside clusters. In the long run, these spillover effects decay faster in outside clusters, but last long for inside cluster. Furthermore, this result changes according to the composition of backers. Our study presents a promising avenue for the application of semantic network analysis to the crowdfunding context

Policy Briefs at the National Level : Deliverable 7.2 of the CASI project

This CASI deliverable 7.2 first presents the issues examined and the process used in the national level policy briefs. Key insights from the policy briefs are presented next, followed by a reflection of the further analytical contributions of the outcomes. Finally, a concluding discussion includes an assessment of the usability of the policy brief process in future endeavours