Social Bot Detection as a Temporal Logic Model Checking Problem
| Authors |
|
|---|---|
| Publication date | 2021 |
| Host editors |
|
| Book title | Logic, Rationality, and Interaction |
| Book subtitle | 8th International Workshop, LORI 2021, Xi'an, China, October 16-18, 2021 : proceedings |
| ISBN |
|
| ISBN (electronic) |
|
| Series | Lecture Notes in Computer Science |
| Event | 8th International Workshop on Logic, Rationality and Interaction, LORI 2021 |
| Pages (from-to) | 158-173 |
| Number of pages | 16 |
| Publisher | Cham: Springer |
| Organisations |
|
| Abstract |
Software-controlled bots, also called social bots, are computer programs that act like human users on social media platforms. Recent work on detection of social bots is dominated by machine learning approaches. In this paper we explore bot detection as a model checking problem. We introduce Temporal Network Logic (TNL) which we use to specify social networks where agents can post and follow each other. In this logic we formalize different types of social bot behavior. These are formulas that are satisfied in a model of a network with bots. We provide a simple algorithm to extract a logical model from a real-life social network. We show that we can reduce TNL to a fragment of linear temporal logic with past and use this to establish the computational efficiency of model checking for social bot detection. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-030-88708-7_13 |
| Other links | https://www.scopus.com/pages/publications/85117106720 |
| Permalink to this page | |
