Using Sentiment Analysis and Data Visualization to explore BBNaija2020.
I recently worked on a side project with the premises that if people on Twitter actually vote based on how they talk about the housemates in their tweets.

What happens if people vote as they tweet? Of course, they don’t but what if they do?
Disclaimer: This project is just a project. It is not sponsored by anyone and neither is it directed towards anymore.

This is simply a sentiment analysis and visualization of tweets, not a deep analysis and might not in any way affect
the ACTUAL votes.
Using the housemates’ names as hashtags, 1000 tweets were collected for each housemates from Sunday to Thursday.

We broke it into 3 categories based on how people directed the tweets; Positive, Negative and Neutral.
Positive tweets: Tweets that says something positive about an housemate.
Negative tweets: Tweets that says something negative about a housemate.

Neutral: Tweets are neither positive nor negative.
Based on the premise that
People with neutral comments about an housemate are indecisive of where they stand concerning a housemate.

By using the relationship
Possible eviction = positive-negative to get the value for least and most likely
to be evicted in the BBnaija.
According to the tweets from Sunday to Thursday, the results is as shown
below with Praise leading the chart and Dora among the last 4.

Based on this, Neo is most likely to be among the bottom four.

We further visualized the data individually.

Who else can’t wait for Ebuka to reveal the votes tonight and who is
looking forward to see what next week tweets will look like?
Data Scrapped, analyzed and visualized: by me( @bamidezy)
Information designer: @prommy15.
@Ebuka @bbnajia2020 #BBNaija #ebuka #DataVisualization