Analyze how bots are used to simulate consensus or public support for a position, product, or person, focusing on the methods to create artificial social proof.

Bots are extensively used to simulate consensus or public support for a position, product, or person by creating artificial social proof. This involves employing various techniques to make it appear as though there is widespread agreement or popularity, even if the support is entirely fabricated. This manipulation is designed to influence the perception of real users, who are often swayed by the apparent consensus or trends that they observe online. One of the most common methods of creating artificial social proof is through inflated engagement metrics. Bot networks are programmed to like, share, retweet, comment, and view content, artificially increasing the numbers associated with posts. For example, if a bot network is promoting a product, the bots may like the product's page, share its content, and comment with positive reviews. If a user sees a product page that has tens of thousands of likes, shares and positive comments, they are more likely to believe that the product is popular and therefore worthwhile, even if the engagement is entirely artificial. This inflated engagement creates a false impression of popularity and legitimacy, influencing users to perceive a product or person as more desirable or accepted than they actually are.

Another frequently used technique is the generation of fake reviews and testimonials. Bot networks are often programmed to create fake accounts and use these accounts to post positive reviews on product pages, service listings, or even in app stores. These reviews appear like those that real customers have posted and therefore can significantly impact potential customers’ trust in a product or service. For example, if a bot network is trying to promote a new restaurant, they would create many fake accounts, and then create positive reviews for that restaurant, describing the great food and service. Potential customers who see many positive reviews might be more likely to choose the restaurant, believing that many other people have already had a good experience. These reviews are an effective way of creating social proof. Similarly, if a bot network is promoting a political figure, the bots would create fake social media accounts and then share messages in support of that political figure. This can create a false impression that the person has more popular support than they actually do.

Coordinated commenting and discussions are also frequently used by bot networks to create artificial social proof. Bots are programmed to comment on posts with positive responses, praise, or affirmations of a particular viewpoint, creating the illusion of widespread agreement. For instance, if a campaign is promoting a particular political position, bots may repeatedly post messages that emphasize the benefits of that position, even while ignoring or minimizing its negative aspects. If a user sees a post with many positive comments in support of a specific viewpoint, they are more likely to agree with that viewpoint as well. These coordinated responses create the impression of unanimous agreement or social consensus, influencing users who might otherwise have different opinions. If the bots are also engaging in discussions, and then amplifying their views, this can sway even the most critical observer.

Bot networks also use strategically created social connections to enhance their artificial social proof. Bots are often programmed to follow each other, creating an interconnected network that makes it appear as if there is widespread user engagement. For instance, a group of bots may follow each other and then like, share and comment on each other’s posts. If a user sees that one account is followed by many other accounts, they are more likely to believe that that account has credibility and authority, even though all of the following might be bot accounts. These fake social connections create a false impression that the bots belong to a large and well connected group that has credibility and authority.

The use of trending hashtags and content is another technique frequently used by bot networks to amplify artificial social proof. Bots will repeatedly include specific hashtags in their posts to make those hashtags more visible and to create the impression that the campaign’s messaging aligns with the trends. The more a hashtag is being used by the bots, the more it will appear to be trending, creating a sense of momentum behind a specific narrative. This creates the illusion that the narrative is gaining popularity, even if it is being driven by artificial activity. This also serves as a gateway to make the message more visible on the social media platform.

In summary, bot networks use a variety of sophisticated techniques, such as inflated engagement metrics, fake reviews and testimonials, coordinated commenting, strategic social connections, and trending hashtags to simulate consensus and create artificial social proof. These methods are all designed to manipulate user perceptions and influence their behavior by creating a false impression of popularity and widespread support. This creates a significant challenge for social media platforms as well as for users to differentiate between real and artificial social proof.