3 research outputs found
Recommending investors for crowdfunding projects
To bring their innovative ideas to market, those embarking in new ventures
have to raise money, and, to do so, they have often resorted to banks and
venture capitalists. Nowadays, they have an additional option: that of
crowdfunding. The name refers to the idea that funds come from a network of
people on the Internet who are passionate about supporting others' projects.
One of the most popular crowdfunding sites is Kickstarter. In it, creators post
descriptions of their projects and advertise them on social media sites (mainly
Twitter), while investors look for projects to support. The most common reason
for project failure is the inability of founders to connect with a sufficient
number of investors, and that is mainly because hitherto there has not been any
automatic way of matching creators and investors. We thus set out to propose
different ways of recommending investors found on Twitter for specific
Kickstarter projects. We do so by conducting hypothesis-driven analyses of
pledging behavior and translate the corresponding findings into different
recommendation strategies. The best strategy achieves, on average, 84% of
accuracy in predicting a list of potential investors' Twitter accounts for any
given project. Our findings also produced key insights about the whys and
wherefores of investors deciding to support innovative efforts
Partisan sharing: Facebook evidence and societal consequences
The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news articles and avoid conflicting ones. We verified four main hypotheses. That is, whether partisan sharing: 1) exists at all; 2) changes across individuals (e.g., depending on their interest in politics); 3) changes over time (e.g., around elections); and 4) changes depending on perceived importance of topics. We indeed find strong evidence for partisan sharing. To test whether it has any consequence in the real world, we built a web application for BBC viewers of a popular political program, resulting in a controlled experiment involving more than 70 individuals. Based on what they share and on survey data, we find that partisan sharing has negative consequences: distorted perception of reality. However, we do also find positive aspects of partisan sharing: it is associated with people who are more knowledgeable about politics and engage more with it as they are more likely to vote in the general elections.Jisun An was supported in part by the Google European Doctoral Fellowship in Social Computing