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TrendFinder is an AI-powered trend monitoring tool and sentiment analysis platform. It functions as a social media content aggregator that collects posts and articles from influencers and websites to identify emerging patterns and industry news.
The main features of ericciarla/trendfinder are: Automated Market Intelligence, Sentiment Analysis Tools, Automated Sentiment Trends Analysis, Trending Topic Detectors, Social Trend Analysis, Social Monitoring Systems, Social Media Monitoring, Social Media Stream Aggregators.
Projects with overlapping indexed features include: maxbbraun/trump2cash — trump2cash is a sentiment-based stock trading bot and social media market monitor. It uses a natural language… bisguzar/twitter-scraper — This project is an unauthenticated web scraper designed to extract public data from the Twitter frontend API. It… yikart/aitoearn — AiToEarn is an artificial intelligence-driven social media management platform designed to centralize content… curiousily/get-things-done-with-prompt-engineering-and-langchain — This project is an educational collection of Jupyter notebooks and guides focused on building applications with the… cocoindex-io/cocoindex — Cocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core… shekhargulati/52-technologies-in-2016 — This project serves as a comprehensive educational repository and technical reference collection, documenting a wide…
trump2cash is a sentiment-based stock trading bot and social media market monitor. It uses a natural language processing sentiment analysis tool to scan real-time social media feeds for mentions of publicly traded companies and translates the emotional tone of that text into automated buy or short stock market orders. The system utilizes a ticker mapping utility to resolve company names, subsidiaries, and brands into valid public stock market ticker symbols. To verify the efficacy of these sentiment-driven signals, it includes an algorithmic trading backtester that evaluates trading strategie
This project is an unauthenticated web scraper designed to extract public data from the Twitter frontend API. It functions as a social media data extractor that simulates browser requests to gather information without the need for official API keys or user account authentication. The tool provides capabilities for gathering public posts, harvesting user profile metadata such as biographies and locations, and retrieving trending topics categorized by geographical region. It can perform targeted content scraping based on specific usernames, hashtags, or search queries. The system manages data
AiToEarn is an artificial intelligence-driven social media management platform designed to centralize content orchestration, audience engagement, and performance analytics. It provides a unified workspace where users can generate, optimize, and schedule content across multiple social networks while automating interactions through intelligent language and media models. The platform distinguishes itself by integrating sentiment analysis to categorize audience engagement and identify purchase intent, allowing for personalized automated responses. It utilizes a credit-based accounting system to m
This project is an educational collection of Jupyter notebooks and guides focused on building applications with the LangChain framework. It serves as a practical resource for developers learning to implement prompt engineering, retrieval-augmented generation, and autonomous agent workflows to create intelligent, context-aware systems. The repository distinguishes itself by providing hands-on tutorials for connecting language models to private datasets and external tools. It covers the end-to-end process of designing structured input templates, orchestrating multi-step task sequences, and main