• Krishna Priya M S
• Eswaran H
• Jeshwanth A
• Kishore S A
• Sowndharayn S J

In the digital era, online petitions have become a vital medium for public expression and societal influence. Effectively managing and prioritizing these petitions presents significant challenges due to their sheer volume and diversity. This paper introduces a system designed to automatically categorize user petitions and flag those of critical importance. Leveraging natural language processing (NLP) and machine learning (ML) techniques, the system analyzes petition content to assign appropriate categories and importance levels. The categorization process employs logistic regression algorithm along with TF-IDF, capturing both contextual and sequential information. For importance flagging, features such as moral, emotional, and cognitive elements are extracted to assess the potential impact and urgency of petitions.. This automated approach not only streamlines petition management but also ensures timely attention to pressing public concerns, enhancing the responsiveness of relevant authorities.

Petition categorization, importance flagging, machine learning, Logistic Regression,Voice Based petiton submission, public engagement.

"PETITION FLOW-AN AI POWERED PATH TO RESOLUTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.c823-c828, March-2025, Available :http://www.jetir.org/papers/JETIR2503299.pdf

"PETITION FLOW-AN AI POWERED PATH TO RESOLUTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppc823-c828, March-2025, Available at : http://www.jetir.org/papers/JETIR2503299.pdf