  Twitter is increasingly used for political, advertising and marketing
campaigns, where the main aim is to influence users to support specific causes,
individuals or groups. We propose a novel methodology for mining and analyzing
Twitter campaigns, which includes: (i) collecting tweets and detecting topics
relating to a campaign; (ii) mining important campaign topics using
scientometrics measures; (iii) modelling user interests using hashtags and
topical entropy; (iv) identifying influential users using an adapted PageRank
score; and (v) various metrics and visualization techniques for identifying
bot-like activities. While this methodology is generalizable to multiple
campaign types, we demonstrate its effectiveness on the 2017 German federal
election.
