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Found 14 papers, 7 papers with code
Can GPT-4 Models Detect Misleading Visualizations?
The proliferation of misleading visualizations online, particularly during critical events like public health crises and elections, poses a significant risk.
Characteristics and prevalence of fake social media profiles with AI-generated faces
Applying this method to a random sample of active Twitter users, we estimate a lower bound for the prevalence of profiles using GAN-generated faces between 0. 021% and 0. 044% -- around 10K daily active accounts.
Constructing Vec-tionaries to Extract Message Features from Texts: A Case Study of Moral Appeals
Using moral content in tweets as a case study, we illustrate the steps to construct the moral foundations vec-tionary, showcasing its ability to process texts missed by conventional dictionaries and word embedding methods and to produce measurements better aligned with crowdsourced human assessments.
Fact-checking information from large language models can decrease headline discernment
Fact checking can be an effective strategy against misinformation, but its implementation at scale is impeded by the overwhelming volume of information online.
Anatomy of an AI-powered malicious social botnet
Large language models (LLMs) exhibit impressive capabilities in generating realistic text across diverse subjects.
Accuracy and Political Bias of News Source Credibility Ratings by Large Language Models
Search engines increasingly leverage large language models (LLMs) to generate direct answers, and AI chatbots now access the Internet for fresh data.
Demystifying Misconceptions in Social Bots Research
Research on social bots aims at advancing knowledge and providing solutions to one of the most debated forms of online manipulation.
CoVaxxy: A Collection of English-language Twitter Posts About COVID-19 Vaccines
In this paper, we present the CoVaxxy dataset, a growing collection of English-language Twitter posts about COVID-19 vaccines.
Social and Information Networks
CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of Modality
Previous studies in multimodal sentiment analysis have used limited datasets, which only contain unified multimodal annotations.
Detection of Novel Social Bots by Ensembles of Specialized Classifiers
The ensemble of specialized classifiers (ESC) can better generalize, leading to an average improvement of 56\% in F1 score for unseen accounts across datasets.
Persona2vec: A Flexible Multi-role Representations Learning Framework for Graphs
Graph embedding techniques, which learn low-dimensional representations of a graph, are achieving state-of-the-art performance in many graph mining tasks.
Neutral bots probe political bias on social media
Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content.
Social and Information Networks Computers and Society
Scalable and Generalizable Social Bot Detection through Data Selection
To ensure model accuracy, we build a rich collection of labeled datasets for training and validation.
Arming the public with artificial intelligence to counter social bots
Researchers have responded by developing AI tools to arm the public in the fight against social bots.
Computers and Society
