Below you'll find several sections containing research related to social botnet creation and detection, as well as some reading about social contagion in online social networks. The approaches to social botnet detection are as varied as the methods for creating them. They vary in complexity, objectives and command-and-control capabilities. It's important to consider that often, if not always, when researching social botnets (especially on Twitter) you're likely to encounter several independent botnet communities that may not share design, objectives or organizational characteristics. Sophisticated social botnets may span platforms, utilize digital personas with a high degree of "digital pedigree" and often have tiers of personas (i.e. bots that only retweet based on topics, some that are semi-automated but with human intervention in certain cases, etc.).
- Signals in Social Supernets
- Signals, cues and meaning
- Predicting Dark Triad Personality Traits from Twitter usage and a linguistic analysis of Tweets
- Predicting Susceptibility to Social Bots on Twitter slides
- Maximizing the Spread of Influence through a Social Network
- Investigating the Observability of Complex Contagion in Empirical Social Networks
- The Signal and the Noise
- The spreading of misinformation online
- The Psychology of Human Misjudgment
- When social bots attack: Modeling susceptibility of users in online social networks
- Network Effects and Personal Influences: The Diffusion of an Online Social Network
- [Detect and Track Latent Factors with Online Nonnegative Matrix Factorization] (https://pdfs.semanticscholar.org/fbcf/c8611ac49d5ad30da313ffe90d39bf98587f.pdf)
- Design and Analysis of a Social Botnet
- A Persona-Based Neural Conversation Model
- The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems
- A Neural Attention Model for Abstractive Sentence Summarization
- A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
- A Graph-Based Semi-Supervised Learning for Question Semantic Labeling
- Data-Driven Response Generation in Social Media
- The DARPA Twitter Bot Challenge
- Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls
- Detecting Clusters of Fake Accounts in Online Social Networks
- An Analysis of Social Network-Based Sybil Defenses
- Predicting political party affiliation from text
- Detecting and Analyzing Automated Activity on Twitter
- Using Sentiment to Detect Bots on Twitter: Are Humans more Opinionated than Bots?
- A New Approach to Bot Detection: Striking the Balance Between Precision and Recall
- New Online Ecology of Adversarial Aggregates: ISIS and beyond
- Salience vs. Commitment: Dynamics of Political Hashtags in Russian Twitter
- Are Social Bots on Twitter Political Actors? Empirical Evidence from a Ukrainian Social Botnet
- Bots and Automation over Twitter during the U.S. Election
- Bots, #StrongerIn, and #Brexit: Computational Propaganda during the UK-EU Referendum
- Virtual Plots, Real Revolution
- Social bots distort the 2016 U.S. Presidential election online discussion
- The 'Star Wars' botnet with >350k Twitter Bots
- This is what a graph of 8k fake Twitter accounts looks like
- The Revolutions Were Tweeted: Information Flows During the 2011 Tunisian and Egyptian Revolutions
- Social Media Mining
- The Rise of Social Bots
- Computing Machinery and Intelligence :-)