You might not know this, but I am the negative-Nancy and OJ is the positive-Patricia in our dynamics, and it’s pretty easy to capture just from the first messages of each day: I’m much more inclined to use terms such as ‘ugh’ and ‘horrible’, while OJ’s vocabulary is far more positive than anyone with slow mornings can expect.

I am not looking so great at the moment, while OJ is getting high marks in relationship-maintenance! With my negative mornings and lower initiative, but I wonder, do I trail behind also when it comes to responsiveness?

The age of connectivity

Something to keep in mind before diving into this section is that we are both millennials (yes, despite me being born in the 80’s — See the diagram I’ve added here), and as such, can be hyper-connected and have our phone as another organ of our body. I actually am hating that and actively trying to disconnect and not keep my phone near me, but that’s also material for a different post!

Generational breakdown. Are you also wondering whether Jesus, Moses and Mohammad were all part of the silent generation that apparently spans anything before 1945? [Source]

Delay distribution of both senders — vast majority of replies happen within 2 minutes from the moment they were received!

Looking at our reply-time distribution it seems that we are actually quite similar, and very responsive (sigh). Considering each bin in this distribution is approximately a 2-minute delay, I do lag a tad behind, but it seems insignificant. What could be interesting to investigate is whether we are more responsive during a specific time of day — this might be more valuable than just a general distribution of our response time! Let’s look below (excuse me for the lack of subplots here, but plotly sure makes it impossible to generate when using heatmaps!):

More details below!

The Y-axis of these heatmaps indicates the time delay between getting a message and replying. The X-axis shows the time of day in which the message was received. The different colors in the heatmap indicate how many messages were sent throughout the year, in the specific time of day (x-axis)and within a specific delay (y-axis). For example, we can see that for messages OJ received at 10am, 156 were answered to within 0–2 minutes. Kapish?

First off, like we saw earlier, most of the communication happens in daytime, around mid-afternoon. As expected, we both are not the fastest to respond to late night messages, and seemingly not too different when it comes to our delay answering any daytime messages: we’re pretty fast in most cases! This will be interesting to look at in a few months, hopefully I will not be as connected as before — and this could be a useful measure.

What am I even talking about?

Content is just as interesting as the statistics we’ve explored so far. BUT it’s also a more personal matter, so I will keep this section minimal :)

Negative Nancy or Positive Patricia?

If you have been reading carefully, you might have noticed that traditionally in this relationship, I am considered the more negative among us. But does this actually reflect in what I say versus what OJ says?

Sentiment analysis of our messages was created using nltk’s built-in VADER, which enables sentiment analysis on natural sentences (mostly social media content). I have locally edited the existing VADER lexicon to match our vocabulary more accurately and include terms in French we use very often to reflect sentiment better. More details at the end.

Seems like it’s a definite no! In fact, when comparing percentage-wise, it actually seems I am a bit less negative than OJ! This is a shocker but the differences are minor. An alternative viewpoint that might reflect the situation better is not my negativity in messaging, but rather — lack of positivity. OJ is clearly more positive, with a whole 28.9% of messages said in positive tone, while I stand a whole 5.7% lower. But this was expected.

Looking at what happens throughout the day (excuse me for inserting this as a photo, it was impossible to insert as a decent subplot!), it seems we don’t demonstrate anything significantly odd, perhaps except for a slight higher presence of negative content from my end in the early morning hours (sigh).