Simmons, Matthew P.
Memes Online: Extracted, Subtracted, Injected, and Recollected
Simmons, Matthew P. (University of Michigan) | Adamic, Lada A. (Universiry of Michigan) | Adar, Eytan (University of Michigan)
Social media is playing an increasingly vital role in information dissemination. But with dissemination being more distributed, content often makes multiple hops, and consequently has opportunity to change. In this paper we focus on content that should be changing the least, namely quoted text. We find changes to be frequent, with their likelihood depending on the authority of the copied source and the type of site that is copying. We uncover patterns in the rate of appearance of new variants, their length, and popularity, and develop a simple model that is able to capture them. These patterns are distinct from ones produced when all copies are made from the same source, suggesting that information is evolving as it is being processed collectively in online social media.
The Social Dynamics of Economic Activity in a Virtual World
Bakshy, Eytan (University of Michigan) | Simmons, Matthew P. (University of Michigan) | Huffaker, David A. (University of Michigan) | Cheng, Chun-Yuen (University of Michigan) | Adamic, Lada A. (University of Michigan)
This paper examines social structures underlying economic activity in Second Life (SL), a massively multiplayer virtual world that allows users to create and trade virtual objects and commodities. We find that users conduct many of their transactions both within their social networks and within groups. Using frequency of chat as a proxy of tie strength, we observe that free items are more likely to be exchanged as the strength of the tie increases. Social ties particularly play a significant role in paid transactions for sellers with a moderately sized customer base. We further find that sellers enjoying repeat business are likely to be selling to niche markets, because their customers tend to be contained in a smaller number of groups. But while social structure and interaction can help explain a seller's revenues and repeat business, they provide little information in the forecasting a seller's future performance. Our quantitative analysis is complemented by a novel method of visualizing the transaction activity of a seller, including revenue, customer base growth, and repeat business.