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What this shows: A high-level overview of the conversation landscape. It identifies dominant narratives, leading voices, and overall tone across media, public, and manipulation-linked sources — providing immediate context before diving into metrics.
What this shows: Tracks the percentage of total impressions that translate into measurable action (clicks, signups, or other conversions). It’s your signal of efficiency — not just visibility, but meaningful audience response.
What this shows: Tracks changes in positive, neutral, and negative tone over time across public, media, and manipulation accounts. Use it to spot when mood shifts occur and whether they align or diverge across audience types.
What this shows: Measures emotional depth and diversity — showing how trust, anticipation, joy, fear, and other signals fluctuate daily. This helps detect when emotional intensity rises (like hype cycles or fear reactions).
What this shows: The total reach generated by each author type (public, media, manipulation). It reveals where the audience is actually seeing content — and whether reach comes from organic credibility or manufactured amplification.
What this shows: The number of distinct users or authors engaging each day. A healthy ecosystem shows steady or rising participation; sudden drops or sharp spikes can reveal inorganic bursts or fatigue.
What this shows: Total number of posts analyzed in the data set. Helps understand scale and overall activity level in the conversation.
What this shows: The overall visibility — total reach of all analyzed posts. Larger numbers indicate broader exposure across the monitored time range.
What this shows: The underlying sentiment among authentic communities. This is the true “baseline mood” once bot and paid activity are filtered out — ideal for tracking real audience trust and support.
What this shows: A gauge of inorganic narrative pressure — showing whether manipulation-linked actors are trending toward positivity or negativity. High values suggest coordinated promotion or pushback.
What this shows: Quantifies organic audience interaction (likes, comments, shares, replies). High public engagement alongside consistent sentiment suggests genuine community resonance.
What this shows: Repeat metric confirming consistency in engagement-to-action behavior (validation for Conversion Rate %).
What this shows: Top recurring entities — people, projects, brands — extracted from text mentions. Larger boxes indicate higher frequency. Useful for mapping which names dominate the narrative ecosystem.
What this shows: Ranks the most influential authors by measurable impact. Great for spotting repeat contributors, sudden new entrants, or creators whose content drives disproportionate visibility.
What this shows: Shows the distribution of measurable influence and mentions across public, media, and manipulation actors. Helps assess how much of the conversation is organic vs. synthetic.
What this shows: Displays the most influential posts and event-driven spikes in conversation metrics. Use these to correlate sentiment or engagement surges with real-world events and narratives.