Swayed by Friends or by the Crowd? (original) (raw)
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To Switch or Not To Switch: Understanding Social Influence in Recommender Systems
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We designed and ran an experiment to test how often people's choices are reversed by others' recommendations when facing different levels of confirmation and conformity pressures. In our experiment participants were first asked to provide their preferences between pairs of items. They were then asked to make second choices about the same pairs with knowledge of others' preferences. Our results show that others people's opinions significantly sway people's own choices. The influence is stronger when people are required to make their second decision sometime later (22.4%) than immediately (14.1%). Moreover, people are most likely to reverse their choices when facing a moderate number of opposing opinions. Finally, the time people spend making the first decision significantly predicts whether they will reverse their decisions later on, while demographics such as age and gender do not. These results have implications for consumer behavior research as well as online marketing strategies.
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Social Influence Effects in Online Product Ratings
Journal of Marketing, 2012
Websites prominently display consumers’ product ratings, which influence consumers’ buying decisions and willingness to pay. Few insights exist regarding whether a consumer's online product rating is prone to social influence from others’ online ratings. Examining this issue, the authors hypothesize that other consumers’ online ratings moderate the effects of positive and regular negative features of product experience, product failure, and product recovery (to address product failure) on the reviewer's online product rating. The results from a model using 7499 consumers’ online ratings of 114 hotels support the hypotheses. Other consumers’ online ratings weaken the effects of positive and regular negative features of product experience but can either exacerbate or overturn the negative effect of product failure, depending on the quality of product recovery. For marketing theory, the findings indicate that consumers who influence others are themselves influenced by other con...
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Exploring Social Network Effects on Popularity Biases in Recommender Systems
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items ranked by popularity has been found to be a fairly competitive approach in the top-N recommendation task. In this paper we explore whether popularity should always be ex- pected to be an effective approach for recommendation, and what causes, factors and conditions determine and explain such effec- tiveness. We focus on two fundamental potential sources of biases in rating data which determine the answer to these questions: item discovery by users, and rating decision. We research the role of social communication as a major source of item discovery biases (and therefore rating biases). We undertake the study by defining a probabilistic model of such factors, and running simulations where we analyze the relationships between the effectiveness of populari- ty and different configurations of social behavior. Keywordssocial networks, evaluation, viral propagation.
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Social Network Influence on Online Behavioral Choices
American Behavioral Scientist, 2014
Social media communication is characterized by reduced anonymity and off-to-online social interactions. These characteristics require scholars to revisit social influence mechanisms online. The current study builds on social influence literature to explore social network and gender effects on online behavior. Findings from a quasi-experiment suggest that both network-related variables and gender are significantly associated with online behavior. Perceived social environment, measured by personal network exposure rate, is more significant than objective reality, measured by frequency of received social messages, in determining behavior. We discuss the implications of social contagion effects on web-based strategic communication—including advertising, political campaigns, and social mobilization. Data limitations and the difficulty of measuring social network influence via social media are also discussed.
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