Explore Citation Analysis and Networks in CitationHub

Most citation tools show links, not reasons.

A clean centered explainer layout that animates four evidence chips in sequence around a subtle hub: 'Intent', 'Context', 'Field', and 'Influence'. Start with thin connected lines, then each chip lights up one by one as if citation links are becoming structured evidence. Use dark background, soft gold accents, white labels, and minimal technical UI styling. Finish with all four chips visible at once.

A premium stat board with five stacked metrics appearing in sequence with subtle counting and separators. Show: '1.8M citation events', '23,479 seed papers', '1.4M citing papers', '21 scientific fields', and 'millions of nodes and edges'. Large bold numbers, smaller labels, minimal research-dashboard aesthetic, black text with gold and rust accents on white.

A two-column analytics composition. Left column shows a simplified world map silhouette with three glowing points and labels 'Countries', 'Cities', 'Affiliations'. Right column shows three compact panels animating in: 'Intent patterns', 'Field behavior', and 'Temporal trends'. Use clean dashboard cards, black text, gold highlights, and rust accent lines on a white background.

Seven intent signals

A bold application matrix with a large centered title 'Intent-aware by design'. Below it, five compact cards animate in with short labels: 'Retrieval', 'Recommendation', 'Impact analysis', 'KG completion', and 'AI co-scientist workflows'. Cards should pulse in one by one with simple connector lines, using black text and small rust accent badges on a gold background.

Open on the core problem: most citation tools show links and counts, but not why papers cite each other. Set up CitationHub as the more explainable alternative.

Introduce the scale and composition of the dataset and platform, giving the viewer confidence that this is a serious resource for technical research workflows.

Cover the main dashboard workflow across several quick interface moments: filters, intent distributions, related papers, and co-cited papers.

Shift into network and graph exploration, emphasizing relationships, semantics, and explainable discovery rather than just visuals.

Show geographic and analytics modules, including maps, affiliations, trends, and comparative views across time and fields.

Land on the seven intent categories and why they matter for ML and retrieval applications.

End with a concise takeaway and invitation to explore the Space. This can sit over product branding or a final product screen.