Simple OSINT script to find Instagram profiles by name and e-mail/phone
The Black Tiger is all in one OSINT Tool, which has the best methods to collect Information about something or someone just by few mouse clicks.
🛰 Your geospatial intelligence tool belt for digital investigations
Your Advanced Twitter stalking tool
Instance and Community Explorer for Lemmy
🍊 Find out how many bots follow any given Twitter acount
A small command line tool and set of functions for studying coordination networks in Twitter and other social media data.
Every analytics tool wants a subscription. And your data. I built Twiligent instead. YouTube stats. Instagram stats. One dashboard. Runs locally on your machine.
📊 OSINT dataset of 10,700+ Twitter/X accounts linked to Islamic Republic influence networks. Metadata-only for CIB research & network analysis.
👥 Social Network Analysis Papers
This repository contains code for the paper "RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media" By J. Gao, S. Han, X. Song, et al. - LREC 2020
🇮🇷 5-Year Historical Sentiment Analysis of Persian Telegram (~1M posts) using Google Gemma 3 (27B) via Ollama. A deep NLP study on public mood, sarcasm, and cultural nuances (1399–1404 SH).
Command-line utility to help researchers collect video metadata from Youtube API
Social Media Analysis for Situation Awareness during Crises (SMASAC) Tutorial
An unsupervised method for target-specific stance detection using embeddings-based clustering and projection techniques. Achieves 90% precision without requiring platform-specific features.
Exploration of BERT-BiLSTM models with Layer Aggregation (attention-based and capsule-routing-based) and Hidden-State Aggregation (attention-based and capsule-routing-based).
Social Media Analysis: Twitter, Facebook, and Youtube.
#FakersGonnaFake: using simple statistical tools and machine learning to audit instagram accounts for authenticity
An LSTM-based sentiment analysis model for classifying text emotions. Built with deep learning techniques to accurately detect and predict sentiment in text data.
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