The project to analyze sentiment in tweets about airlines was developed to offer an interactive and engaging interface using Streamlit. The purpose of the application is to enable users to view tweets classified according to the type of sentiment - positive, negative or neutral - in order to analyze public perceptions in real time. With this tool, it is possible to explore how people feel about airlines and get a clearer picture of what is being discussed on social networks.

One of the app’s main features is the presentation of interactive graphs, such as barplots and pie charts, which illustrate the distribution of sentiment among tweets. These visualizations allow a quick comparison between the different types of sentiment, facilitating data analysis. The flexibility in choosing the visualization format is a strong point, allowing the user to customize the way they explore the data according to their needs and preferences.

In addition, the application offers the possibility of carrying out a temporal and geographical analysis of tweets. The user can select a specific time interval and observe the number of tweets posted during that period. It is also possible to visualize the geographical distribution of opinions by means of an interactive map, which provides a more in-depth understanding of how opinions about airlines vary between different countries.

The project also includes a comparison between airlines, displaying bar graphs that show the number of tweets and the sentiments related to each company. This feature is very useful for marketing professionals and managers, who can analyze the performance of their brands on social networks. The inclusion of a word cloud, generated from the sentiments associated with the tweets, offers a detailed view of the most commented topics, allowing companies’ strengths and weaknesses to be identified, as well as providing valuable data for improving strategies and the customer experience.

The video below, in Portuguese, shows the app implemented.



App for viewing

https://us-airline-sentiment.streamlit.app/

Project repository

https://github.com/diogo-dantas/us-airline-sentiment

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