To perform an analysis on Elon Musk's Twitter data from 2010-2022, with a focus on the years 2017-2022, the following steps can be taken:
Data Collection: Collecedt Twitter data for Elon Musk from 2010-2022, and filter out all tweets except for those from the years 2017-2022.
Data Preprocessing: Cleaned and preprocessed the text data by removing punctuation and stop words, and convert all words to lowercase.
Word Frequencies: Computed the frequency of each word for each year (2017-2022).
Top 10 Words: Displayed the top 10 words for each year, based on their frequency.
Histograms: Plot histograms of word frequencies for each year to visualize the distribution of word frequencies.
Zipf's Law: Used Zipf's Law to plot log-log plots of word frequencies and their rank for each year, to see if there is a power-law relationship between the two variables.
Bigram Network Graphs: Created bigram network graphs for each year to visualize the co-occurrence of words in tweets, and identify any patterns or trends.
By performing these steps, we can gain insights into the language and topics that Elon Musk has been discussing on Twitter over the past few years, and how they have evolved over time.