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Haode-Sun/Sentiment-Analysis-of-Leeds-EV-Charging-Stations-Comments-Based-on-Zap-Map

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Sentiment-Analysis

Introduction

The increasing adoption of electric vehicles (EVs) in the UK is expected to increase given their potential contribution to reduce greenhouse gases and dependency on fossil fuels.The UK Government's Smart Charging Action Plan for electric vehicles explains that by 2030 there will be up to 10 million electric vehicles on roads, as the UK speeds ahead on its journey to net zero.As of 1 January 2023, there were 37,055 public electric vehicle charging devices installed in the UK, compared to 1 October 2022,total installed devices increased by 2,418, an increase of 7%. The geographical distribution of charging equipment within the UK is uneven. Some UK local authorities have bid for UK government funding for charging equipment, while others have not. Much of this infrastructure provision is market-driven, with individual charging networks and other businesses (such as hotels) choosing where to install equipment(Official Statistics, 2023). As a result, the charging experience for users varies due to factors such as the speed of charging, frequency of servicing and location distribution of equipment at charging stations.

This project will be based on data from the Zap-Map platform, using Leeds as a scope, to analyse the sentiment of user reviews of electric vehicle charging stations. We will create word clouds of comments, counting the most frequent words in the comments; we then Calculate Polarity and Subjectivity on these comments to be used to determine whether a comment expresses a positive, negative or neutral view, which allows the user's attitude to be determined by quantifying the sentiment of the text. Finally, we used NRCLex to conduct a sentiment analysis of the main types of sentiment in the comments and to create a sentiment map to explore the spatial distribution of sentiment.

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