NLP based grievance redressal system for Indian Railways

TL;DR

This paper proposes an NLP-based software plugin to assist Indian Railways in automatically analyzing tweets for complaints, aiming to reduce human effort in the grievance redressal process.

Contribution

It introduces a novel NLP-driven tool to identify complaints in tweets, enhancing the efficiency of the existing Indian Railways grievance system.

Findings

The plugin effectively classifies complaint-related tweets.

It reduces manual effort in complaint analysis.

The system improves response time for grievance handling.

Abstract

The current grievance redressal system has a dedicated 24X7 Twitter Cell, wherein the human experts take actions and respond to the tweets of customers addressed to Ministry of Railways. It is done quite promptly by the human experts. It is understood that the software plugin to process the tweets addressed towards Ministry of Railways can not match the human expertise. Still, efforts can be done to build a software plugin which can ease the human effort. This project aims at building a software plug-in to minimize the human effort involved in analysis of tweets addressed to Indian Railways and aid in existing complaints redressal system by identifying the complaints from the tweets. It is understood that it is not possible to match human promptness in terms of handling the tweets, still we can try to reduce the human efforts by working on the following objectives: 1.