Analysing twitter sentiment and topics
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Analysing tweeter sentiment and topics
One of the things that I enjoy in my spare time is to learn and explore the wolrd of NLP tools. Thus, I decided to explore the possibilities of a simple model to simplify my twitter experiece. Tweet_analyser applies natural language processing (NLP) models to analyze the sentiment and polarity of tweets in a given Twitter list. The library then generates a report that highlights the main topics being discussed and the correlation between the keywords used. This information can be enhance your Twitter experience by giving you the broader picture or jst keep up-to-date on a particular topic without having to dive in the timeline.
One of the key features of Tweet_analyser is its ability to identify the top tweets and the most relevant tweets in a given Twitter list. This feature can be particularly useful for someone looking to engage with others on Twitter. By identifying the most popular tweets and the ones that are most likely to discuss a topic of interest, one can better grasp the mood.
Finally, the tool is designed to run once a day on schedule, which might be very handy for a quick snap of the news, rather than the overstimulation of the timeline. It also appears in your email as a newsletter so it suits nicely in a work routine.
You can download the code at my github.
You can also see the a sample report 