2377 People Like this Article: The Influence of Others’ Decisions on Yours

2377 People Like this Article: The Influence of Others’ Decisions on Yours Yasuaki Sakamoto (ysakamot@stevens.edu) Jing Ma (jma1@stevens.edu) Jeffrey V. Nickerson (jnickerson@stevens.edu) Center for Decision Technologies School of Technology Management, Stevens Institute of Technology Hoboken, NJ 07030 USA Abstract like. Other users can digg or bury the submitted stories to vote for or against the stories. Users cannot digg the same story twice. Each digg reflects a user’s liking of a story, and the total number of diggs for a story represents the popularity of the story. Digg displays the total number of diggs associated with each story. Digg promotes a story to the front page once it gains a certain number of supporters within a certain timeframe, and the story becomes prominent. Through this process, some stories collect a large number of votes. What drives people’s voting behavior? Do they vote for stories based on the interestingness of the stories? Or do they vote for stories based on how many others already support the stories? Does the information about the number of supporters a story already has influence one’s perception of the interestingness of the story? We address these questions. How do people make decisions about their preferences? We examine how others’ opinions affect one’s decisions. In Experiment 1, we found that popular online news stories were not inherently interesting, suggesting that something other than the content of the stories was driving people’s liking of the stories. In Experiments 2 and 3, we manipulated information about how previous readers rated the stories. Participants in Experiment 2 rated the same stories as more or less interesting depending on whether they were told that those stories were rated high or low by others. In Experiment 3, more participants preferred the stories that were actually less popular when they received pseudo-information that more people liked those stories. Taken together, our results suggest that others’ decisions can greatly influence not only people’s decisions but also their actual liking and opinions. Examining how people’s decisions influence and are influenced by others’ decisions can shed light on how trend, culture, and community develop. The Influence of Others Keywords: Social learning; trends; conformity; decision making; interestingness; preference; social networks Introduction Did you like this story? Which wine do you like? Many online sites ask this type of question to gather data on people’s opinions. Through these collective opinions, some items become widely popular and trends emerge. How do people make decisions about their preferences? Some stories and wines may be inherently better than others, and people may prefer those with higher quality. In many situations, however, the quality of the items may be similar, and people may make decisions based on what others think about the items, rather than the content of the items. Furthermore, other individuals’ opinions may influence one’s perception of the item. In the present work, we examine how others’ opinions affect one’s decisions. One unique aspect of the present work is that we examine decision-making behavior in an online community. Better understanding of how people make decisions in online environments is important because many individuals now use community-based Web services, such as Digg and Delicious. These new technologies allow users to share information with other individuals (Glushko et al., 2008), and thus the opinions of others are readily available in online environments. We use Digg (digg.com) as an example. In Digg, users submit the Uniform Resource Locators of Web stories they People often rely on other individuals’ decisions to make their own (e.g., Cialdini & Goldstein, 2004). People may conform to other people’s decisions because of their desire to make correct decisions under uncertainty (Sherif, 1935). Alternatively, people may adopt other people’s decisions due to their desire to be liked and to not appear deviant (Asch, 1951). Another possibility is that people simply imitate the behavior of others (e.g., Gureckis & Goldstone, 2006). Imitation can increase people’s efficiency by allowing them to try out solutions that they would not have considered otherwise (Bandura, 1965). Frequently imitated solutions are usually useful, and thus people may develop the expectation that solutions selected by more people are the useful ones. Indeed, organizations tend to adopt changes that are adopted most frequently by other organizations (Kraatz, 1998). People develop culture by adopting others' innovations (Dennett, 1995). Consistent with these previous findings from social influence research, Salganik, Dodds, and Watts (2006) found that whereas good music was always popular (i.e., downloaded by many) and bad music was always unpopular, the popularities of the pieces in between could vary depending on whether or not the number of downloads the pieces had was publicly available. In our previous computer simulation work, a model that assumed that users followed other users’ decisions did a good job of accounting for the popularity of news stories in Digg (Sakamoto et al.,