Use minimum objective or subjective probability

When selecting instances for active learning, we may be very sure that
the instance is positive or negative, but not so sure if the instance is
objective or subjective. This shouldn't usually be the case, but in case
there is this discrepancy we should have those instances rated uncertain
as well.
Fix: handle error response from Twitter search
Allow requiring tweet results to have a location

By allowing to search for tweet results by location, we lay the
foundation for getting location specific statistics about keywords. This
is progress towards gh-44.
Add: location sentiment stats using Google Charts

When the geo-option is specified, the average sentiment for each country
is calculated and displayed on a map using the geochart visualization
from Google Charts. This closes gh-44.

Improvements can still be made. First, the number of geocoded tweets
returned for each keyword search is very low, therefore even popular
terms have little data. Additional pages of results may be retrieved,
but this will use many API calls and may result in being rate limited.
The second current drawback is the estimation of country from the geo-
coordinates.
Increase geo search range and number of results

We get more results by retrieving more pages of results, however we run
a greater risk of being rate limited.
Cache geo Twitter results separately from non-geo
Allow geo-option to be selected using checkbox
Allow forcing query to be classified as-is
Make count-option useful when geo-option used

When the geo-option is selected, we change the meaning of the
count-option from number of results per pages to the number of result
pages to retrieve. We do this because the amount of geocoded tweets per
page is very low.