Why use logged variables?

Probably, this is a very basic question but I don't seem to be able to find a solid answer for it. I hope here, I can.

I'm currently reading papers as a preparation for my own master's thesis. Currently, I'm reading a paper which researches the relationship between tweets and stock market features.

In one of their hypothesis, they propose that "increased tweet volume is associated with an increase in trading volume".

I would expect them, in the pairwise correlations, to correlate tweetVolume with tradingVolume, but instead they report using the logged versions: LN(tweetVolume) and LN(tradingVolume).

For my thesis, I have replicated this bit of their paper. I have collected tweets about 100 companies for over 6 months (tweetVolume) and stock trading volume for the same timeframe. If I correlate the absolute variables, I find r=.282, p.000 but when I use the logged verions, I find r=.488, p=.000.

I don't understand why researchers sometimes use logged versions of their variables and why correlation seems so much higher if you do so. What is the reasoning here, and why is it OK to use logged variables?

Your help is greatly appreciated :-)