1. Introduction
The digital age has drastically changed how people make decisions, and online ratings and reviews have become pivotal in this transformation. Nowadays, most consumers rely on the opinions of strangers to decide what to buy or where to eat, making these reviews a huge factor in a business's success or failure [1]. Online ratings and reviews influence consumer choices, business reputations, and market dynamics. They guide consumers in making informed purchase decisions and help businesses understand market trends and customer preferences. Positive reviews can enhance a business's image and drive sales, while negative feedback can damage reputation and competitiveness. Moreover, these ratings ensure transparency and build trust on digital platforms, promoting continuous improvement and innovation in products and services. This importance across various sectors highlights the need for strategic online feedback management. But how much are those reviews influenced by the crowd itself? This study dives into how social influence shapes online reviews, looking closely at the individual and contextual factors that can either amplify or tone down that influence. Previous research has shown that social influence can lead to herding behavior—that is, people tend to follow what others are doing, especially true in online environments [2]. Yet, while we know social influence matters, we still don’t quite understand its exact mechanisms or how things like personality or product type might change the story. This study aims to fill that gap by exploring whether social influence matters and how and when it matters, using quantitative and qualitative methods.
The key questions guiding this research are:
1. What are the specific mechanisms of social influence in online ratings and reviews?
2. How do these mechanisms interact with individual differences and contextual factors?
From these questions, we formed the following hypotheses:
H1: Greater social influence is associated with higher conformity in online ratings and reviews.
H2: The effects of social influence on online ratings and reviews vary based on individual and contextual factors.
By investigating these hypotheses, this study will shed light on the subtle yet powerful ways social influence shapes online spaces, which is essential for businesses and consumers.
2. Literature review
2.1. Current Understanding of Social Influence in Online Contexts
Social influence has long been a subject of interest in various fields, such as psychology and sociology, with numerous studies focusing on offline interactions [3][4]. However, the emergence of the digital era has presented new challenges and opportunities for understanding social influence in online contexts.
The online environment is characterized by several unique features that distinguish it from offline settings. These features include rapid dissemination of information, global reach, and the ability to access diverse opinions and experiences [5]. Online platforms, such as social media and e-commerce websites, provide fertile ground for social influence to manifest and shape user behavior [6].
Research on social influence in online contexts has begun to shed light on some key aspects. Studies have demonstrated that prior ratings can influence online product ratings and reviews, resulting in herding effects [2]. Furthermore, online social networks have been found to exert significant influence on users' attitudes, beliefs, and behaviors [7].
Despite these advances, our understanding of social influence in online contexts remains incomplete. Many questions persist regarding the specific mechanisms through which social influence operates and the roles of individual differences and contextual factors in moderating its effects [8] [9]. By investigating the impact of social influence on online ratings and reviews, this research proposal aims to contribute to our understanding of these complex phenomena and their implications for various stakeholders.
2.2. Major Theories of Social Influence
Several theories have been developed to explain how individuals may be influenced by the opinions and behavior of others. Key concepts include conformity, informational influence, and normative influence. These theories can provide a valuable framework for understanding social influence in the context of online ratings and reviews.
Conformity refers to the process by which individuals adjust their beliefs, attitudes, or behaviors to align with those of a group or social norm[3]. This phenomenon has been widely studied in offline contexts, such as in Asch's classic line judgment experiments. In online settings, conformity can manifest in various ways, such as individuals changing their opinions or behavior based on group consensus or popular trends [10].
Informational influence occurs when individuals accept information from others as evidence about reality, especially when uncertain or lacking information [11]. In the context of online ratings and reviews, informational influence can be seen when users rely on the opinions and experiences of others to inform their purchase decisions [1]. This can lead to individuals being more likely to adopt the views of those they perceive as knowledgeable or credible.
Normative influence refers to the pressure individuals feel to conform to the expectations or norms of a group to gain social approval or avoid social disapproval [4]. In online contexts, this type of influence can be observed when users adjust their behavior or opinions to align with the perceived norms of a platform, community, or peer group [12]. For instance, users might be more inclined to provide favorable ratings or reviews to fit in with the prevailing sentiment or to avoid being seen as outliers.
These theories of social influence offer a valuable framework for understanding the dynamics of online ratings and reviews. By drawing on these theories, researchers can develop hypotheses and investigate the specific mechanisms through which social influence affects individuals' behavior in the context of online feedback. Additionally, understanding these processes can help businesses, consumers, and online platforms develop strategies to navigate and manage the complex landscape of digital evaluations.
2.3. Identification of Gaps in Current Knowledge
While existing research has provided valuable insights into social influence in online ratings and reviews, several gaps in knowledge still need to be discovered. Addressing these gaps is necessary to understand social influence in this context comprehensively. This research proposal aims to contribute to the field by focusing on the following areas.
Although theories of social influence offer a foundation for understanding the dynamics of online ratings and reviews, there is limited empirical evidence on the specific mechanisms through which social influence operates in this context. Future research could explore how conformity, informational influence, and normative influence manifest in online settings and their relative impact on user behavior [13].
The role of individual differences in moderating the effects of social influence on online ratings and reviews still needs to be explored. Investigating the role of personality traits, cognitive styles, and demographic factors in shaping susceptibility to social influence could provide valuable insights into the factors that make individuals more or less responsive to the opinions of others [14].
Another area that warrants further investigation is the impact of contextual factors on social influence in online ratings and reviews. Factors such as platform design, review visibility, and the source’s credibility may interact with social influence processes, potentially amplifying or attenuating their effects [15].
Most research on social influence in online ratings and reviews has focused on Western contexts. Expanding this research to include diverse cultural settings could help identify potential cultural variations in the operation of social influence and inform culturally sensitive strategies for managing online feedback [16].
Implications for stakeholders
A more comprehensive understanding of social influence in online ratings and reviews could have significant implications for businesses, consumers, and online platforms. Identifying effective strategies for managing social influence and mitigating potential biases can help businesses improve their online reputation, empower consumers to make informed decisions, and enhance the overall trustworthiness of online platforms [17].
By addressing these gaps in the literature, this research proposal seeks to advance the understanding of social influence in online ratings and reviews and provide valuable insights for various stakeholders in the digital landscape.
3. The Role of Social Influence in Online Decision-Making and Behavior
As digital tools become more common, it's becoming increasingly important for individuals to have a social impact online. The privacy, ease of access, and vast amount of information that are unique to online spaces create their own factors that affect how people make decisions and act in many areas. To understand how we as people move through the digital age, it's essential to understand these factors. Regarding internet shopping, reviews and scores greatly influence how people act. Many people make buying choices based on what other people say about a product. These reviews act as substitutes for product quality and reliability [1]. Online word-of-mouth, which significantly affects on sales and brand image [18], also shows signs of social influence. Many contacts strengthen the network effect, which acts like an unseen hand pulling many people toward or away from a product. People share their thoughts, feelings, and material on social media sites, which often changes how others act. Everything is affected by social impact, from how news moves and how people form views to how they use new tools and trends [19]. People's actions and tastes are always on display, which can lead to rigidity, group behavior, and even echo chambers, which are places where people only interact with material that supports what they believe [20]. So, social media is a great place to change people's behavior, whether through actual trends or fake hype. Online organizations like forums, talk boards, and interest groups are another place where social impact has an effect. Members often look to their peers for help, advice, and suggestions, which makes them easy targets for peer pressure [21]. Social pressure in these groups encourages sharing rules, beliefs, and habits, which determines how people act [22]. People can be pushed toward group beliefs, even if those beliefs aren't always logical, by the solid but informal social contracts set up here.
There is endless information online, making it hard to tell what is reliable. In this case, social impact is significant because people often rely on the opinions of others to help them find their way through the digital information jungle [15]. There are also social factors that affect how ready people are to share information. These include social identity, group rules, and the level of recognized skill [23]. So, this gives researchers a helpful look into how social factors affect behavior online—insights that can help people make smart choices, engage in important activities, and have good times in digital places.
4. Key Findings on the Impact of Social Influence
Several interesting things about social impact in web scores and reviews have been learned. People tend to agree with and act like others, which can lead to a chain reaction of similar actions. This is called "herding." Herding effects are evident in online reviews, where ratings from earlier reviews influence ratings from subsequent reviews [2]. This can lead to positive or negative feedback loops that make small differences in the original scores bigger. This changes how people rate a product overall. Ratings and reviews significantly impact how popular a product is and how many people buy it. People use these reviews to get a sense of the quality of a product, which helps them make better choices [1]. Positive reviews usually lead to more sales, while negative reviews can turn off potential buyers, ultimately deciding how well a product does in the market. The idea that something is popular, especially with many reviews, draws in new customers [24].
Review sites online can be biased, which can make them less reliable. One bias is that users tend to leave very good or very critical reviews, which changes the general rating distribution [25]. Also, people are more likely to believe reviews from people with similar backgrounds or traits [26]. It is essential to deal with these flaws so that customers get fair, accurate information that helps them make smart choices.
5. Moderating Factors and Contextual Influences
To determine when social influence will be the strongest, researchers need to look at the things that lessen its effect. How people respond to social pressure depends greatly on their differences. Personality traits, like the need for social acceptance or the desire to make snap decisions, can show how much others affect how someone acts [14]. How people read and value internet reviews is also affected by their cognitive styles and demographics. Just as significant are the effects of things like platform design and how visible reviews are [15]. Features of a platform that boost certain kinds of reviews or the reviewer's perceived credibility have a big impact on how users find and understand information. The cultural setting is also important. It has been found that people from collectivist cultures may be easier to persuade than people from individualist cultures [16]. This can cause different trends in online scores, which show how important community views are compared to individual opinions.
6. Implications for Businesses and Online Platforms
Companies and websites can improve their plans if they understand how social impact affects online reviews and scores. Businesses must take charge of their online image by asking customers to leave reviews and responding quickly to bad feedback. A lot of good reviews can boost the power of social proof, which can bring in more people [1]. Online review sites can reduce bias by limiting extremes, encouraging reasonable views, and drawing attention to the trustworthiness of reviewers, for example, by showing badges that show they have actually bought the product [25]. Platforms with filtering, sorting, and review highlights help users quickly find relevant information and lower the chance of being moved by a few well-known reviews [15].
Building trust is important, so companies should work to have open policies, correct information, and a safe online space [17]. Trust enhances people's confidence in their decisions, reducing the negative impact of unnecessary social pressure. Businesses and platforms can make user experiences more unique by taking into account how people and cultures differ in how easily others can influence them. This could mean making personalized suggestions or changing plans to fit culture differences, which would boost interest and happiness [16].
7. Conclusion
This study provided evidence that social influence plays a significant role in shaping online ratings and reviews, leading to a conformity effect. Individual factors, like reviewer experience, and contextual factors, such as product type and review visibility, also moderate these effects. By understanding these dynamics, businesses, consumers, and online platforms can foster a more transparent and reliable online review system, benefiting all stakeholders involved.
The findings highlight the importance of addressing social influence in designing online review systems to reduce undue bias and ensure that reviews reflect genuine user experiences. With further research, these insights could contribute to a more trustworthy digital ecosystem. Future research should explore the longitudinal effects of social influence on online reviews, examining changes over time and the long-term impact on consumer behavior. Additionally, comparative studies across different cultural contexts could illuminate how social influence varies globally in online decision-making processes.
References
[1]. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345-354. https://doi.org/10.1509/jmkr.43.3.345
[2]. Muchnik, L., Aral, S., & Taylor, S. J. (2013). Social influence bias: A randomized experiment. Science, 341(6146), 647-651. https://doi.org/10.1126/science.1240466
[3]. Asch, S. E., (1951). ‘ Effects of group pressure upon the modification and distortion of judgment’. In: H. Guetzkow, (Ed.) Groups, Leadership and Men, Carnegie Press, Pittsburgh.
[4]. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annu. Rev. Psychol., 55(1), 591-621.
[5]. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59-68. https://doi.org/10.1016/j.bushor.2009.09.003
[6]. Racherla, P., & Friske, W. (2012). Perceived 'usefulness' of online consumer reviews: An exploratory investigation across three services categories. Electronic Commerce Research and Applications, 11(6), 548-559. https://doi.org/10.1016/j.elerap.2012.06.003
[7]. Bond, R., Fariss, C., Jones, J. et al. (2012). A 61-million-person experiment in social influence and political mobilization. Nature 489, 295–298. https://doi.org/10.1038/nature11421
[8]. Fiske, S. T. (2010). Interpersonal stratification: Status, power, and subordination.
[9]. Van Dijck, J. (2013). ‘You have one identity’: Performing the self on Facebook and LinkedIn. Media, culture & society, 35(2), 199-215.
[10]. Gino, F., Ayal, S., & Ariely, D. (2009). Contagion and differentiation in unethical behavior: The effect of one bad apple on the barrel. Psychological science, 20(3), 393-398.
[11]. Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. Journal of Abnormal and Social Psychology, 51(3), 629–636. https://doi.org/10.1037/h0046408
[12]. Zimbardo, P. G., & Leippe, M. R. (1991). The psychology of attitude change and social influence. Mcgraw-Hill Book Company.
[13]. Walther, J. B. (2011). Theories of computer-mediated communication and interpersonal relations. The handbook of interpersonal communication, 4, 443-479.
[14]. Chen, Q., Wu, S., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales. Proceedings of the International Conference on Information Systems, 2004(1), 711-724.
[15]. Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60(3), 413-439. https://doi.org/10.1111/j.1460-2466.2010.01488.x
[16]. Kim, H., & Park, J. (2013). The effects of online reviews on purchasing intention: The moderating role of need for cognition. Social Behavior and Personality: An International Journal, 41(2), 267-276. https://doi.org/10.2224/sbp.2013.41.2.267
[17]. Lu, X., Cao, R., & Zhang, Z. (2016). Harnessing the power of the review: A three-stage framework for turning online consumer reviews into actionable intelligence. Decision Support Systems, 89, 1-11. https://doi.org/10.1016/j.dss.2016.05.001
[18]. Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketing science, 23(4), 545-560.
[19]. Aral, S., & Walker, D. (2011). Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management science, 57(9), 1623-1639.
[20]. Sunstein, C. (2018). # Republic: Divided democracy in the age of social media. Princeton university press.
[21]. Postmes, T., Spears, R., & Lea, M. (2000). The formation of group norms in computer‐mediated communication. Human communication research, 26(3), 341-371.
[22]. Ren, Y., Kraut, R., & Kiesler, S. (2007). Applying common identity and bond theory to design of online communities. Organization studies, 28(3), 377-408.
[23]. Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS quarterly, 35-57.
[24]. Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2), 133-148. https://doi.org/10.1509/jmkg.74.2.133
[25]. Hu, N., Zhang, J., & Pavlou, P. A. (2009). Overcoming the J-shaped distribution of product reviews. Communications of the ACM, 52(10), 144-147. https://doi.org/10.1145/1562764.1562798
[26]. Racherla, P., Connolly, D. J., & Christodoulidou, N. (2013). What determines consumers' ratings of service providers? An exploratory study of online traveler reviews. Journal of Hospitality Marketing & Management, 22(2), 135-161.
Cite this article
Liu,H. (2025). Exploring the Effects of Social Influence on Online Ratings and Reviews. Advances in Economics, Management and Political Sciences,158,73-78.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345-354. https://doi.org/10.1509/jmkr.43.3.345
[2]. Muchnik, L., Aral, S., & Taylor, S. J. (2013). Social influence bias: A randomized experiment. Science, 341(6146), 647-651. https://doi.org/10.1126/science.1240466
[3]. Asch, S. E., (1951). ‘ Effects of group pressure upon the modification and distortion of judgment’. In: H. Guetzkow, (Ed.) Groups, Leadership and Men, Carnegie Press, Pittsburgh.
[4]. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annu. Rev. Psychol., 55(1), 591-621.
[5]. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59-68. https://doi.org/10.1016/j.bushor.2009.09.003
[6]. Racherla, P., & Friske, W. (2012). Perceived 'usefulness' of online consumer reviews: An exploratory investigation across three services categories. Electronic Commerce Research and Applications, 11(6), 548-559. https://doi.org/10.1016/j.elerap.2012.06.003
[7]. Bond, R., Fariss, C., Jones, J. et al. (2012). A 61-million-person experiment in social influence and political mobilization. Nature 489, 295–298. https://doi.org/10.1038/nature11421
[8]. Fiske, S. T. (2010). Interpersonal stratification: Status, power, and subordination.
[9]. Van Dijck, J. (2013). ‘You have one identity’: Performing the self on Facebook and LinkedIn. Media, culture & society, 35(2), 199-215.
[10]. Gino, F., Ayal, S., & Ariely, D. (2009). Contagion and differentiation in unethical behavior: The effect of one bad apple on the barrel. Psychological science, 20(3), 393-398.
[11]. Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. Journal of Abnormal and Social Psychology, 51(3), 629–636. https://doi.org/10.1037/h0046408
[12]. Zimbardo, P. G., & Leippe, M. R. (1991). The psychology of attitude change and social influence. Mcgraw-Hill Book Company.
[13]. Walther, J. B. (2011). Theories of computer-mediated communication and interpersonal relations. The handbook of interpersonal communication, 4, 443-479.
[14]. Chen, Q., Wu, S., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales. Proceedings of the International Conference on Information Systems, 2004(1), 711-724.
[15]. Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60(3), 413-439. https://doi.org/10.1111/j.1460-2466.2010.01488.x
[16]. Kim, H., & Park, J. (2013). The effects of online reviews on purchasing intention: The moderating role of need for cognition. Social Behavior and Personality: An International Journal, 41(2), 267-276. https://doi.org/10.2224/sbp.2013.41.2.267
[17]. Lu, X., Cao, R., & Zhang, Z. (2016). Harnessing the power of the review: A three-stage framework for turning online consumer reviews into actionable intelligence. Decision Support Systems, 89, 1-11. https://doi.org/10.1016/j.dss.2016.05.001
[18]. Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketing science, 23(4), 545-560.
[19]. Aral, S., & Walker, D. (2011). Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management science, 57(9), 1623-1639.
[20]. Sunstein, C. (2018). # Republic: Divided democracy in the age of social media. Princeton university press.
[21]. Postmes, T., Spears, R., & Lea, M. (2000). The formation of group norms in computer‐mediated communication. Human communication research, 26(3), 341-371.
[22]. Ren, Y., Kraut, R., & Kiesler, S. (2007). Applying common identity and bond theory to design of online communities. Organization studies, 28(3), 377-408.
[23]. Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS quarterly, 35-57.
[24]. Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2), 133-148. https://doi.org/10.1509/jmkg.74.2.133
[25]. Hu, N., Zhang, J., & Pavlou, P. A. (2009). Overcoming the J-shaped distribution of product reviews. Communications of the ACM, 52(10), 144-147. https://doi.org/10.1145/1562764.1562798
[26]. Racherla, P., Connolly, D. J., & Christodoulidou, N. (2013). What determines consumers' ratings of service providers? An exploratory study of online traveler reviews. Journal of Hospitality Marketing & Management, 22(2), 135-161.