Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
Deeper sentiment analysis using machine translation technology
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatically classifying documents by ideological and organizational affiliation
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Improving the language of influence
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Most analysis of influence looks at the mechanisms Used, and how effectively they work on the intended audience. Here we consider influence from another perspective: what do the language choices made by influencers enable us to detect about their internal mental state, strategies and assessments of success. We do this by examining the language used by the U.S. presidential candidates in the high-stakes attempt to get elected. Such candidates try to influence potential voters, but must also pay attention to the parallel attempts by their competitors to influence the same pool. We examine seven channels: persona deception, the attempt by each candidate to seem as attractive as possible, nouns, as surrogates for content; positive and negative language; and three categories that have received little attention, verbs, adverbs, and adjectives. Although the results are preliminary, several intuitive and expected hypotheses are supported, but some unexpected and surprising structures also emerge. The results provide insights into related influence scenarios where open-source data is available, for example marketing, business reporting, and intelligence.