In this step, we calculate the sentiment of each tweet. We create the new table
groups the tweets of
l3 view on the basis of id, sums up the polarity of each word and assigns each
tweet a sentiment label such as positive, negative, or neutral.
What is the sentiment of tweet with id as
Launch hive console by typing the
hive command in the web console.
tweets_sentiment table. Each row of `tweets_sentiment table stores the sentiment of the tweet. Run below command in the Hive on your web console
create table tweets_sentiment stored as orc as select id, case when sum( polarity ) > 0 then 'positive' when sum( polarity ) < 0 then 'negative' else 'neutral' end as sentiment from l3 group by id;
Sample rows of
tweets_sentiment table are
Note - Having trouble with the assessment engine? Follow the steps listed here