• Mitesh Trivedi

In traditional ways, traffic related and road and transport related issued are highlighted and detected by mostly physical place visit in most of the world. New research area aims to use Social Media data and Classification techniques to detect Road and Transport Related issues. As current work has been done using Twitter data using Word2Vec classification algorithm to detect various issues at major cities of India. During our research work we plan to use Social Media Data and News Data with Word2Vec classification algorithm. We also intend to include tweets from local languages .We also planned to apply Word2Vec classification for Multi-Class Classification Problem and NLP for feature extraction. We have used cosine similarity function to find similarity among tweets and after find similarity we have obtained result from tweets into positive, negative, neutral with the help of semantic analysis.

Data Mining, Python,, Word2Vec, Social Media, Event Detection, Semantic Analysis, Cosine Similarity

"Traffic issues categorization of Indian Cities using Word2Vec by Social Media Data ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 6, page no.576-580, June-2020, Available :http://www.jetir.org/papers/JETIR2006421.pdf

"Traffic issues categorization of Indian Cities using Word2Vec by Social Media Data ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp576-580, June-2020, Available at : http://www.jetir.org/papers/JETIR2006421.pdf