Following the preceding post, I’ve dug a little deeper into sentiment viz to explore more carefully what it might offer in terms of revealing the emotional components within Twitter and tweets. Like before, I used a chat hashtag as the search term and perhaps unsurprisingly got a similar shaped visualisation which expressed sentiment as generally positive and somewhat relaxed. Probing a little further and clicking on a few individual circles provides the data which located the tweet at that point on the chart. Here we see the overall sentiment rating expressed as ‘v’ for valence (how pleasant) and ‘a’ for arousal (how activated). Then there’s a breakdown of those words which contributed to that sentiment rating, with their individual scores. We therefore have multiple ways we can compare the emotional content of one tweet with another, but can make a judgement whether those ratings make sense – more of that later.