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Found 21 papers, 10 papers with code
Embedding Structured Dictionary Entries
Previous work has shown how to effectively use external resources such as dictionaries to improve English-language word embeddings, either by manipulating the training process or by applying post-hoc adjustments to the embedding space.
MMVAE at SemEval-2022 Task 5: A Multi-modal Multi-task VAE on Misogynous Meme Detection
The challenge of misogynous meme detection is to co-represent multi-modal features.
Racist or Sexist Meme? Classifying Memes beyond Hateful
Memes are the combinations of text and images that are often humorous in nature.
Collaborative Content Moderation in the Fediverse
The Fediverse, a group of interconnected servers providing a variety of interoperable services (e. g. micro-blogging in Mastodon) has gained rapid popularity.
Exploring the Use of Abusive Generative AI Models on Civitai
To explore this, we conduct the first comprehensive empirical study of an AIGC social platform, focusing on its use for generating abusive content.
Exploring the Capability of ChatGPT to Reproduce Human Labels for Social Computing Tasks (Extended Version)
To evaluate ChatGPT's potential, we re-annotate seven datasets using ChatGPT, covering topics related to pressing social issues like COVID-19 misinformation, social bot deception, cyberbully, clickbait news, and the Russo-Ukrainian War.
How Similar Are Elected Politicians and Their Constituents? Quantitative Evidence From Online Social Networks
We find that elected politicians tend to be equally similar to their constituents in terms of content and style regardless of whether a constituency elects a right or left-wing politician.
Learning Domain-Invariant Features for Out-of-Context News Detection
In order to effectively adapt the detection model to unlabeled news topics or agencies, we propose ConDA-TTA (Contrastive Domain Adaptation with Test-Time Adaptation) which applies contrastive learning and maximum mean discrepancy (MMD) to learn domain-invariant features.
Decentralised Moderation for Interoperable Social Networks: A Conversation-based Approach for Pleroma and the Fediverse
Recent work has exploited the conversational context of a post to improve this automatic tagging, e. g. using the replies to a post to help classify if it contains toxic speech.
APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPT
To address this, there has been a flurry of research into prompt tuning -- techniques and guidelines that attempt to improve the quality of prompts.
Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks
We believe this work can open up new lines of analysis and act as a basis for future research into the exploitation of ChatGPT for human annotation tasks.
Lady and the Tramp Nextdoor: Online Manifestations of Economic Inequalities in the Nextdoor Social Network
We collect 2. 6 Million posts from 64, 283 neighborhoods in the United States and 3, 325 neighborhoods in the United Kingdom, to examine whether online discourse reflects the income and income inequality of a neighborhood.
Twitter Dataset for 2022 Russo-Ukrainian Crisis
Such information sharing campaigns can range from spreading factual information to propaganda and misinformation.
Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors
We find that (i) commercial antivirus engines are vulnerable to AMM-guided test cases; (ii) the ability of a manipulated malware generated using one detector to evade detection by another detector (i. e., transferability) depends on the overlap of features with large AMM values between the different detectors; and (iii) AMM values effectively measure the fragility of features (i. e., capability of feature-space manipulation to flip the prediction results) and explain the robustness of malware detectors facing evasion attacks.
An Expert Annotated Dataset for the Detection of Online Misogyny
Online misogyny is a pernicious social problem that risks making online platforms toxic and unwelcoming to women.
Analyzing Temporal Relationships between Trending Terms on Twitter and Urban Dictionary Activity
However, it is unclear exactly how activity on this platform relates to larger conversations happening elsewhere on the web, such as discussions on larger, more popular social media platforms.
Urban Dictionary Embeddings for Slang NLP Applications
The choice of the corpus on which word embeddings are trained can have a sizable effect on the learned representations, the types of analyses that can be performed with them, and their utility as features for machine learning models.
A First Instagram Dataset on COVID-19
We believe that this contribution will help the community to better understand the dynamics behind this phenomenon in Instagram, as one of the major social media.
Social and Information Networks
Characterising User Content on a Multi-lingual Social Network
In the case of images containing text that cross language barriers, we see that language translation is used to widen the accessibility.
Challenges in the Decentralised Web: The Mastodon Case
The Decentralised Web (DW) has recently seen a renewed momentum, with a number of DW platforms like Mastodon, Peer-Tube, and Hubzilla gaining increasing traction.
Networking and Internet Architecture Cryptography and Security Computers and Society
WhatsApp, Doc? A First Look at WhatsApp Public Group Data
In this dataset paper we describe our work on the collection and analysis of public WhatsApp group data.
Social and Information Networks
