Intellectual Property India Publishes Patent Application for System And Method For Context-Aware Sentiment Analysis Of Social Media Data With Adaptive Brand Reputation Scoring

MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202621108267 A) filed by Punam Yogesh Patil; Mrs. Punam Parag Toke; Dr. Shriram N. Kargaonkar; Mrs. Harshada Suyog Deshpande; Kamini Pravin Fulpagar; Dr. Santosh Devidas Pandure; and Ms. Ashwini Sanjay Gagare on September 09, 2026, for System And Method For Context-Aware Sentiment Analysis Of Social Media Data With Adaptive Brand Reputation Scoring.

Inventors include Punam Yogesh Patil; Mrs. Punam Parag Toke; Dr. Shriram N. Kargaonkar; Mrs. Harshada Suyog Deshpande; Kamini Pravin Fulpagar; Dr. Santosh Devidas Pandure; and Ms. Ashwini Sanjay Gagare.

The application for the patent was published on October 30, 2026, under issue no. 44/2026.

Abstract: ABSTRACT SYSTEM AND METHOD FOR CONTEXT-AWARE SENTIMENT ANALYSIS OF SOCIAL MEDIA DATA WITH ADAPTIVE BRAND REPUTATION SCORING [044] A computer-implemented system and method are disclosed for context-aware sentiment analysis of heterogeneous social-media data and adaptive determination of brand reputation. Social-media items are normalized into evidence objects, monitored brand entities and sentiment targets are resolved, and target-specific sentiment is determined using contextual and, where available, multimodal features. A reliability engine weights evidence according to semantic relevance, attribution confidence, model uncertainty, cross-modal agreement, novelty, and independence. A coordination detector identifies duplicated, synchronized, or otherwise dependent content and attenuates cluster contribution according to effective independent evidence. A temporal event graph associates evidence with brand- related events, while an adaptive scoring engine separates persistent reputation from event-shock effects and adjusts event decay according to persistence, recurrence, and source diversity. The resulting reputation state may include a reputation value, momentum, event-shock value, uncertainty, and explanatory factors, thereby reducing distortion from target ambiguity, coordinated amplification, transient events, and uncertain classifications. Accompanied Drawing [FIGS. 1-2]

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