Method

My method for collecting this data is downloading Verizon's bill. One can see their text message usage from this. If I were better at coding, I would try to write an application that extracted the text message data (date time, number, person, content). But, I am not a good coder at all. And I do not want to download someone else's app...who knows what they would do with my information!

Also, my work shift is Tuesday through Saturday, 1600 to 0000; I have a forty-five-minute commute. Any texts in that commute time are sent from Google Voice!

High-Level Results

This table speaks for itself. A small decrease of texts in August and almost the same amount!

When Are My Active Hours?

I received and sent at least one text message every hour during the month of August. I must be a robot because I do not sleep! With that said, it looks like I usually fall asleep between 0400 to 0500 and then wake up at 1100. Although, I still send a lot of messages between 0500 to 1100...what the heck!

I communicate the most at 0100, although most people reply at 1100. Apparently, they sleep at 0100.

What Happens During the Weekdays?

Mondays and Thursdays were my most active days to text overall. During these two days, 38.61% of my texts were received and 38.24% of my texts were sent.

I texted on Mondays at a different peak hour of 2300. This means for the whole week, about 65% of my texts during 2300 were on Monday, even though they were only 20% of my total texts on Monday.

Thursdays’ peak time is more consistent with the rest of the week. At 1200, I received 17.4% and sent 17.63% of my texts for Thursday. During this time period on Thursday, the texts make up 40% of the entire weeks’ 1200 (time) texts.

As we can see, I do not have a consistent sleep schedule. Mondays have an entirely different off-peak time and I somehow text a bunch on Thursdays at noon. I wonder what is so interesting on Thursdays!?

Top 10 Communicators

Brandon 1 and Colin make up 35% of my texts received and 39% of my texts sent. Holy cow I text them a ton!

Oh and my mom is number 9! Hi mom!

Brandon 1 and Colin have the same peak days as the entire week: Monday and Thursday.

By combining Brandon 1’s and Colin’s texts, I know that 40% of my texts that I receive and are from/to them on Mondays. On Thursdays, 23% of my texts are from them and 30% of texts are to them.

I do text Brandon 1 and Colin during similar peak hours as the rest of the week: 2300 on Mondays and 0100 on Thursdays.

The Averages

Although Brandon and Colin’s peak weekdays and times were Monday & Thursday and 2300 and 0100, I wonder what the rest of the week looks like? The highest average, if you will.

On average, I received 249 and sent 297 texts during the week & received 72 and sent 87 texts per hour.

On Monday and Thursday, I had the highest average of received and sent texts.

During the hours of 1100 and 1200, I had the highest average amount of received texts, while 0100 and 1100 had the highest average sent.

Conclusion

I think the overall conclusion is I am crazy for keeping track of all of this data. What will I do with it? Make these reports! I think this small case study allowed me to explore what my data can do. It also gives me a better idea of how to answer any questions I have about it.

When I get around to it, I think it will be interesting to see the rankings of everyone and how they change over time. As some may know, life moves forward and people come in and out of your life. I can see that in action through my text messaging, which is very interesting to me.

Come on over to the Google Sheet to check out the Pivot Tables and raw data.

Google Sheet

PDF of this Case Study