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ericciarla avatar

ericciarla/trendFinder

0
View on GitHub↗
4,021 stars·439 forks·TypeScript·MIT·20 views

TrendFinder

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 system utilizes large language models to process collected web data and determine the relevance of trending topics. It operates as an automated notification system, delivering contextual alerts and source links to messaging platforms when significant online activity is detected.

The platform covers automated market intelligence and real-time trend alerts by monitoring social content on a schedule. It includes capabilities for AI trend analysis and social media monitoring to track product releases and market sentiment.

Features

  • Automated Market Intelligence - Monitors web targets and social platforms to maintain updated summaries of market trends and competitor activity.
  • Sentiment Analysis Tools - Processes collected web data using LLMs to classify the emotional tone and relevance of trending topics.
  • Automated Sentiment Trends Analysis - Uses large language models to process collected text and identify overarching sentiment trends.
  • Trending Topic Detectors - Provides real-time detection of trending topics from live data sources using AI-powered extraction.
  • Social Trend Analysis - Analyzes viral patterns and trending content feeds on social media platforms using AI.
  • Social Monitoring Systems - Tracks real-time social media activity and influencer posts on a schedule to monitor industry news.
  • Social Media Monitoring - Tracks influencer posts and discussions across social media platforms to identify new product releases.
  • Social Media Stream Aggregators - Aggregates and deduplicates content from multiple social media sources and influencer websites.
  • Notification Systems - Provides an automated framework to trigger and dispatch trend alerts to users across digital channels.
  • Messaging Notifications - Delivers automated notifications with trend context and source links to messaging platforms.
  • Event-Driven Notification Triggers - Implements automated alerts dispatched to external messaging platforms when specific trend thresholds are detected.
  • External API Polling - Periodically queries social media APIs and websites at fixed intervals to collect new activity data.

Star history

Star history chart for ericciarla/trendfinderStar history chart for ericciarla/trendfinder

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does ericciarla/trendfinder do?

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.

What are the main features of ericciarla/trendfinder?

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.

Which projects share features with ericciarla/trendfinder?

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…

Projects sharing features with TrendFinder

These projects share indexed features with TrendFinder. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
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  • bisguzar/twitter-scraperbisguzar avatar

    bisguzar/twitter-scraper

    4,013View on GitHub↗

    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

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  • yikart/aitoearnyikart avatar

    yikart/AiToEarn

    21,287View on GitHub↗

    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

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  • curiousily/get-things-done-with-prompt-engineering-and-langchaincuriousily avatar

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    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

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