Showing papers by "Duncan J. Watts published in 2010"

Predicting consumer behavior with Web search

Abstract: Recent work has demonstrated that Web search volume can “predict the present,” meaning that it can be used to accurately track outcomes such as unemployment levels, auto and home sales, and disease prevalence in near real time. Here we show that what consumers are searching for online can also predict their collective future behavior days or even weeks in advance. Specifically we use search query volume to forecast the opening weekend box-office revenue for feature films, first-month sales of video games, and the rank of songs on the Billboard Hot 100 chart, finding in all cases that search counts are highly predictive of future outcomes. We also find that search counts generally boost the performance of baseline models fit on other publicly available data, where the boost varies from modest to dramatic, depending on the application in question. Finally, we reexamine previous work on tracking flu trends and show that, perhaps surprisingly, the utility of search data relative to a simple autoregressive model is modest. We conclude that in the absence of other data sources, or where small improvements in predictive performance are material, search queries provide a useful guide to the near future.

Financial incentives and the "performance of crowds"

Abstract: The relationship between financial incentives and performance, long of interest to social scientists, has gained new relevance with the advent of web-based "crowd-sourcing" models of production. Here we investigate the effect of compensation on performance in the context of two experiments, conducted on Amazon's Mechanical Turk (AMT). We find that increased financial incentives increase the quantity, but not the quality, of work performed by participants, where the difference appears to be due to an "anchoring" effect: workers who were paid more also perceived the value of their work to be greater, and thus were no more motivated than workers paid less. In contrast with compensation levels, we find the details of the compensation scheme do matter--specifically, a "quota" system results in better work for less pay than an equivalent "piece rate" system. Although counterintuitive, these findings are consistent with previous laboratory studies, and may have real-world analogs as well.

Inferring relevant social networks from interpersonal communication

Abstract: Researchers increasingly use electronic communication data to construct and study large social networks, effectively inferring unobserved ties (e.g. i is connected to j) from observed communication events (e.g. i emails j). Often overlooked, however, is the impact of tie definition on the corresponding network, and in turn the relevance of the inferred network to the research question of interest. Here we study the problem of network inference and relevance for two email data sets of different size and origin. In each case, we generate a family of networks parameterized by a threshold condition on the frequency of emails exchanged between pairs of individuals. After demonstrating that different choices of the threshold correspond to dramatically different network structures, we then formulate the relevance of these networks in terms of a series of prediction tasks that depend on various network features. In general, we find: a) that prediction accuracy is maximized over a non-trivial range of thresholds corresponding to 5-10 reciprocated emails per year; b) that for any prediction task, choosing the optimal value of the threshold yields a sizable (~30%) boost in accuracy over naive choices; and c) that the optimal threshold value appears to be (somewhat surprisingly) consistent across data sets and prediction tasks. We emphasize the practical utility in defining ties via their relevance to the prediction task(s) at hand and discuss implications of our empirical results.

Real and Perceived Attitude Agreement in Social Networks

Abstract: It is often asserted that friends and acquaintances have more similar beliefs and attitudes than do strangers; yet empirical studies disagree over exactly how much diversity of opinion exists within local social networks and, relatedly, how much awareness individuals have of their neighbors' views. This article reports results from a network survey, conducted on the Facebook social networking platform, in which participants were asked about their own political attitudes, as well as their beliefs about their friends' attitudes. Although considerable attitude similarity exists among friends, the results show that friends disagree more than they think they do. In particular, friends are typically unaware of their disagreements, even when they say they discuss the topic, suggesting that discussion is not the primary means by which friends infer each other's views on particular issues. Rather, it appears that respondents infer opinions in part by relying on stereotypes of their friends and in part by projecting their own views. The resulting gap between real and perceived agreement may have implications for the dynamics of political polarization and theories of social influence in general.

Prediction without markets

Abstract: Citing recent successes in forecasting elections, movies, products, and other outcomes, prediction market advocates call for widespread use of market-based methods for government and corporate decision making Though theoretical and empirical evidence suggests that markets do often outperform alternative mechanisms, less attention has been paid to the magnitude of improvement Here we compare the performance of prediction markets to conventional methods of prediction, namely polls and statistical models Examining thousands of sporting and movie events, we find that the relative advantage of prediction markets is surprisingly small, as measured by squared error, calibration, and discrimination Moreover, these domains also exhibit remarkably steep diminishing returns to information, with nearly all the predictive power captured by only two or three parameters As policy makers consider adoption of prediction markets, costs should be weighed against potentially modest benefits

Cooperation and Contagion in Networked Public Goods Experiments

Abstract: A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of web-based experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. This result implies either that individuals are not conditional cooperators, or else that cooperation does not benefit from positive reinforcement between connected neighbors. We then tested both of these possibilities in two subsequent series of experiments in which artificial "seed" players were introduced, making either full or zero contributions. First, we found that although players do generally behave like conditional cooperators, they are as likely to decrease their contributions in response to low contributing neighbors as they are to increase their contributions in response to high contributing neighbors. Second, we found that positive effects of cooperation are not contagious. In total we report on 113 human subjects experiments, highlighting the speed, flexibility, and cost-effectiveness of web-based experiments over those conducted in physical labs.

Six Degrees: The New Science of Networks

Abstract: A central objective of this course is to help you to think about real-world social, cultural, economic, organizational, ecological, and technological problems in a different way. To this end, instead of a term paper, you will be required to submit at the end of the semester, a "scrap book" of annotated clippings from the media. This project is not meant to be arduous—in fact, it is intended to be fun—and you can approach it in many different ways. The main objectives are (a) to encourage you to keep abreast of current events, as well as contemporary ideas and trends; and (b) to help you take the concepts of the course out of the classroom and use them to interpret the world around you.

Using the web to do social science

Abstract: Social science is often concerned with the emergence of collective behavior out of the interactions of large numbers of individuals, but in this regard it has long suffered from a severe measurement problem - namely that individual-level behavior and interactions are hard to observe, especially at scale and over time. In this talk, I will argue that the technological revolution of the Internet is beginning to lift this constraint. To illustrate, I will describe several examples of internet-based research that would have been impractical to perform until recently, and that shed light on some longstanding sociological questions. Although internet-based research still faces serious methodological and procedural obstacles, I propose that the ability to study truly "social" dynamics at individual-level resolution will have dramatic consequences for social science.