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Game Theory in Auctions

This year, Paul Milgrom and Robert Wilson have won the 2020 Nobel Economics Prize for their important contributions to auction theory and inventions of new auction formats that we are using today.

Now let me introduce auctions with some examples:

Let’s say you know that a burger usually costs $10 at McDonald’s, and you are very hungry at the moment. But would you go to MacDonald’s and directly tell the cashier that you are willing to pay more for a burger since you are hungry? No. Because your hunger is private information to you only, you would rather get the food at the regular price.

What happens if this time you are the food seller? Would you ever tell the customer the minimum price of a burger you are willing to sell when you know it will sell more than the minimum price? You wouldn’t. Because that’s private information to you again.

A classic situation of an auction happens when you are competing with several other buyers, then the seller would prefer to sell the limited item to the buyer with the highest bid. Under this situation, each buyer will gradually reveal his/her highest private value that he/she is willing to pay to win the auction item.

Simplified payoff matrix of license auction

Private information makes auctions interesting. From the perspective of game theory, no one would know the exact payoffs from the strategies that bidders made since the private values are very subjective to each of the bidders. So, what should bidders do? With the question in mind, Milgrom and Wilson started the research to analyze how different bidders behave strategically when they each have access to different information during auctions. In 1969, Wilson recognized that the Nash equilibrium concept would permit an analysis of auctions with common value, meaning that part of the auction item’s true value is equal to all potential bidders while having the other part as the different private values.

Private and common values in auctions also lead to a well-known phenomenon called “the winner’s curse”. That is, the winner wins the auction only when his/her bid is higher than anybody else. This indicates that the winner’s bid may exceed the true value of the item a lot which ends up in a loss on the transaction.

Therefore, how to make a wise choice in an auction that balances the risks and the probability of winning the auction is always a challenging topic. And hopefully, with the knowledge of game theory, we can find out the best strategies in every “auction” in our life.

References:

Popular information. NobelPrize.org. Nobel Media AB 2020. Sat. 21 Nov 2020. <https://www.nobelprize.org/prizes/economic-sciences/2020/popular-information/>

BBC News. “Nobel: US Auction Theorists Win Economics Prize.” BBC News, BBC, 12 Oct. 2020, www.bbc.com/news/business-54509051.

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Your Facebook Friend may be evil bots

            Online Social Networks (OSNs) provide conveniences to connect people online. For example, a popular social media platform like Facebook has over 2.5 billion monthly active users. But are you aware of the users you are connected with might not be a real person?

Social Bots – opportunity or threat?

            A research group at the University of British Columbia conducted an infiltration test on Facebook with a Socialbot Network where researchers operated social engineering bots to gain access to users’ personal information such as birthday, addresses, and phone numbers. They started with creating fake user accounts and profiles for the bots. Each social bot was automated and linked to a Facebook account. Social bots could make posts and sending friend requests. Then, these bots tried to mimic real users’ activities and make as many friends as possible. Because most of the Facebook users publish their personal information to their friends only.

Triadic Closures Are the New Black - DZone Database
Triadic closure in social networks

            Then, things get interesting as the social engineering strategy that bots used was to send friend requests to the friends of their friends they already had. This was related to the triadic closure principle which shows that if the connections between A-B and B-C exist, then there is a tendency for the new connection A-C to be formed. This strategy increased the likelihood of accepting bots’ friend requests about three times higher given the existence of mutual friends.

            The research group had to take down the bots since they caused heavy traffic to Facebook and resulted in a successful acceptance rate of 80% after 8 weeks of starting the experiment. With this large-scale infiltration, it is easy to collect users’ personal information for malicious purposes such as identity theft. To further elaborate on the experiment, we can see that it is dangerous to leave our sensitive information on OSNs like Facebook. The protection that Facebook used did not appear to be effective in detecting social bots, and this is only one of the vulnerabilities in the network. Defending against such threats will be just the first step in maintaining a safer network.

References

Fruhlinger, J. (2019, September 25). Social engineering explained: How criminals exploit human behavior. Retrieved October 23, 2020, from https://www.csoonline.com/article/2124681/what-is-social-engineering.html

Maffei, K. (n.d.). Six Degrees: The Science of a Connected Age by Duncan Watts. Retrieved October 23, 2020, from https://serendipstudio.org/complexity/course/emergence06/bookreviews/kmaffei.html

Boshmaf, Y., Muslukhov, I., Beznosov, K., & Ripeanu, M. (2011, September 27). The Socialbot Network: When Bots Socialize for Fame and Money. Retrieved October 23, 2020, from http://lersse-dl.ece.ubc.ca/record/258?ln=en