Analyzing Public Sentiment on Law Enforcement Issues across Social Media Platforms: A Comprehensive Data Collection and NLP Approach

Abstract

Utilization, data mining, and sentiment analysis. This study strives to efficiently gather data while adhering to privacy policies and performing data normalization for consistent cross-platform analysis. The use of Natural Language Processing (NLP) techniques is critical in processing and analyzing the acquired texts. This encompasses processes like tokenization, stopword removal, stemming, lemmatization, Named Entity Recognition (NER), Part-of-Speech (POS) Tagging, sentiment analysis, and topic modeling. The application of NLP aims to enhance research efficiency and unveil in-depth insights from complex data, necessitating human evaluation to ensure accuracy and relevance.