Review public posts, Reels, and carousels matching tracked hashtags. Explore likes, comments, sentiment trends, accounts, hashtags, and locations.
Hear the Echo. Understand the Story.
Monitor selected keywords, hashtags, and public Facebook Pages across six data sources. Explore content, engagement, sentiment predictions, and entities in one dashboard.
Six supported data sources • Topic-based monitoring • Scheduled data updates
Collection schedules and available metrics vary by data source.

Track selected keywords, hashtags, and public Facebook Pages.
Echora is extending LLMs across machine-learning prediction workflows for all six data sources.
Data refresh frequency varies by source.
Explore content volume, engagement, sentiment predictions, and source-specific signals.
Analytics Across Six Supported Data Sources
Monitor selected topics across the public content Echora can collect from each platform.
Twitter / X
Review keyword-matched posts, reposts, replies, likes, sentiment and volume trends, top accounts, words, and entities.
Online News
Find articles surfaced for monitored keywords. Echora extracts and cleans article text where available, then organizes results by sentiment, category, outlet, and entities.
YouTube
Explore public videos matching tracked keywords by views, likes, comment counts, channel, and category. Sentiment predictions use video titles.
TikTok
Explore keyword-matched videos by views, likes, comments, shares, saves, sentiment trends, estimated creator gender, and popular sounds.
Monitor selected public Pages and analyze their posts by engagement, sentiment, and reaction mix.
LLM-Powered Predictions Across Six Data Sources
Echora is extending LLMs across its machine-learning prediction workflows for all six supported data sources. Available prediction types vary with the content and metadata provided by each platform.
Sentiment Prediction
Prediction workflows classify analyzed text as positive, neutral, or negative. Language, context, and the source content can affect the result.
Named Entity Extraction
Extracts entity mentions and their predicted types from analyzed content. Echora groups matching labels so teams can review which people, organizations, and places appear most often.
Topic Categorization
Where category classification is supported, prediction workflows can assign topic labels such as politics, economy, or technology to analyzed content.
Cross-Source Rollout
LLM-based machine-learning predictions are intended for all six supported data sources. Each pipeline can use prediction tasks suited to its available text and metadata.
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