Introduction

This comparative analysis looks at 2 of the most recent generations: Millennials and Generation Z. This analysis uses twitter to compare the 2 generations and will use mainly a sentimental analysis to see what is being said about the 2 generations on twitter. The sentimental analysis will look at the positive and negative words that are being used in tweets that mention either Millennials or Gen Z. Millennials are mostly seen as individuals born between 1981-1996 and Generation Z are for individuals born between 1997-2012 Both generations are active on twitter - so this should be fun!

First Analysis

Let’s look at 2,000 tweets in which 1,000 tweets mention the generation “millennial” and 1,000 tweets mention the generation “Gen Z.” The period that we pulled these tweets are from 5:30 PM on October 30th and 10:00 PM on November 3rd.

Our first question we want to answer is how each generation’s tweets compares regarding their emotional sentiment. To do this we dive into the 2,000 tweets and break down each word that was used in the tweet (removing stop words such as “a” “is” etc.) and classify the word used in the tweet to a specific sentiment class. The classes are trust, fear, negative, sadness, anger, surprise, positive, disgust, joy, and anticipation.

Let’s take a look!

From the above visualization we see very similar patterns between the two generations in each sentiment. The biggest differences between the two generations are in the anticipation and positive sentiments. Gen Z is roughly 75 points higher in anticipation and roughly 60 higher in the positive sentiments.

Anticipation is the one that really sticks out given such the difference between the two generations. As we know Gen Z is the generation after Millenials, which obviously makes this generation younger in age. Therefore, we can possible make the inference that this generation through these tweets has higher optimism than Millenials due to life opportunities that can be coming up such as college, new relationships, and new job/career etc.

Next Sentiment Analysis: Postive and Negative Words

We would like to find out which generation (when mentioned in a tweet) has more positive words assigned to the tweet than the other. We would also like to see the number of negative words as well. This question will give us a better idea in regard to the positivity or negativity that is used when the generation is talked about on twitter. To do this let’s look at each tweet’s words and use sentimental analysis to assign a word (not using stop words like “a”, “is” etc.) to either positive or negative.

Below is a table showing the number of positive and negative words used:

## # A tibble: 4 × 3
##   Class       sentiment Tweets
##   <chr>       <chr>      <int>
## 1 Gen Z       negative     397
## 2 millennials negative     381
## 3 Gen Z       positive     258
## 4 millennials positive     239

From the table above we see that for both millennials and Gen Z more words were assigned to the sentiment of negative than positive. This is not a small difference either. For Gen Z over 60% of the words were assigned a negative sentiment, and for millennials it was over 61%.

To further analyze the negative and positive sentiments for each class, it would be wise for us to look at the specific words to see which negative and positive words were used most often in the tweets for millennials and Gen Z.

The above chart shows us words that were used over 10 times in the tweets we pulled that mentioned millennials and Gen Z. This visual is very interesting as we see that the generations differ regarding the common words and their sentiment. For example, there were 4 negative words used over 10 times for Millennials that were not used over 10 times for Gen Z. The word “debt” really sticks out as many millennials have finished schooling and are known to take out large student loans to help pay for college. This word was used 17 times in the tweets mentioning millennials. Also, words such as “killing”, “blame”, and “ruining” were used by tweets mentioning millennials, but were not shown as being used over 10 times with tweets mentioning Gen Z. Now looking at Gen Z, we see that some of the negative words that were used in their tweets could be seen as crueler than the negative words assigned to millennials (words such as shit, dying, hate, wrong). Finally, the biggest difference between Gen Z and millennials regarding commonly used word is the word “love.” Love was used 18 times more than tweets mentioning Gen Z. Further investigation would need to be conducted to get an understanding of why the positive and negatives stood out from the tweets within the period there were collected.

Time Analysis

We want to know if the sentiment changes by the day and the hour of the day. First lets look at the day of the week:

Are we more negative or positive on a specific day?

We see that Gen Z was mentioned on Saturday through Wednesday, while millennials were only mentioned on one day. All days had more words classified as negative than positive. However, Monday and Saturday were not as negative as the other days.

Sentiment broken down by Hour in the Day

From the visual above we see that tweets that mention millenials are showing at around 13 hours (or 1pm EST). We don’t see any blue bars before this time. This is because it took less time to retrieve 1,000 tweets mentioning millenials compared to millenials, which tells us that the word millenial is being used more on twitter than Gen Z (at least this time period). It is very interesting to see that most hours for Gen Z tweets resulted in negative sentiments. There were just 5 hours out of the day which resulted in more postivie words being said about Gen Z than negative words.

Conclusion

Overall, it is interesting to view tweets on twitter that mention both generations. Most of the tweets were assigned a negative sentiment, and the words that were used most for the two generations differed. We also noticed that it took much less time to pull 1,000 tweets for millennials than it did for Gen Z. More investigation can be done to get a better understanding of the differences between the tweets for millennials and Gen Z, but this analysis gives us a good idea of the sentiment being used regarding the two generations.