Mood of the nation - week one
Mood of the nation - week one
Stuff found out
There are several tools available for exploring the Twitter API. I used a combination of the web search, the apigee console and twurl.
Twitter's search API only contains tweets from the last 6-9 days.
Topsy API is available for historical data but it is pretty expensive. The trial could be used but has a limit of 1000 tweets in total so there is little point in using that.
More research about the available data might have been a good idea before pitching the idea.
Clearly, historical sentiment analysis is something that is in demand. At least enough for a company to exist that charges pretty large sums of money in order to access the data. And Twitter are not going to do it for free.
The term 'NHS' had over 250K tweets in the past 30 days according to Topsy
Incoming changes
Now I am aware that historical sentiment analysis is not feasible due to financial restrictions (I am not going to stump up any cash until I figure out something that could provide a return on the investment!). I need to pivot. I see there are two choices:
Start collecting relevant data on a daily/weekly basis so I will have some historical data to use at a later date.
Look at 'real-time' analysis. Rather than work from a historical base - use the data that twitter makes available through the search API i.e. the last 6-9 days. This could then be tied to into the streaming API.
At this moment in time I am leaning towards using what is available i.e. the data in the search API
Future work
The focus for next week will be on understanding how to do sentiment analysis on the tweets. Options include doing this myself or using an existing service like Sentiment140. Once that is done it will be about tying that into other data such as geographic region of the tweet and other interesting data sets.














