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In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter. This was the most popular sentiment analysis shared task to date with more than 40 teams participating in each of the last three years. This year's shared task competition consisted of five sentiment prediction sub-tasks. Two were reruns from previous(More)
This paper discusses the fourth year of the " Sentiment Analysis in Twitter Task ". SemEval-2016 Task 4 comprises five sub-tasks, three of which represent a significant departure from previous editions. The first two subtasks are reruns from prior years and ask to predict the overall sentiment, and the sentiment towards a topic in a tweet. The three new(More)
We investigate whether wording, stylistic choices, and online behavior can be used to predict the age category of blog authors. Our hypothesis is that significant changes in writing style distinguish pre-social media bloggers from post-social media blog-gers. Through experimentation with a range of years, we found that the birth dates of students in college(More)
It has long been established that there is a correlation between the dialog behavior of a participant and how influential he or she is perceived to be by other discourse participants. In this paper we explore the characteristics of communication that make someone an opinion leader and develop a machine learning based approach for the automatic(More)
This paper explores the task of building an accurate prepositional phrase attachment corpus for new genres while avoiding a large investment in terms of time and money by crowd-sourcing judgments. We develop and present a system to extract prepositional phrases and their potential attachments from ungrammati-cal and informal sentences and pose the(More)
Sentence fusion enables summarization and question-answering systems to produce output by combining fully formed phrases from different sentences. Yet there is little data that can be used to develop and evaluate fusion techniques. In this paper, we present a methodology for collecting fusions of similar sentence pairs using Amazon's Mechanical Turk,(More)
This paper explores the automatic detection of sentences that are opinionated claims, in which the author expresses a belief. We use a machine learning based approach, investigating the impact of features such as sentiment and the output of a system that determines committed belief. We train and test our approach on social media, where people often try to(More)
Determining when conversational participants agree or disagree is instrumental for broader conversational analysis; it is necessary , for example, in deciding when a group has reached consensus. In this paper , we describe three main contributions. We show how different aspects of conversational structure can be used to detect agreement and disagreement in(More)
We present two supervised sentiment detection systems which were used to compete in SemEval-2014 Task 9: Sentiment Analysis in Twitter. The first system (Rosenthal and McKeown, 2013) classifies the polarity of subjective phrases as positive, negative, or neutral. It is tailored towards online genres, specifically Twitter, through the inclusion of(More)
Social transmission of information is vital for many group-living animals, allowing coordination of motion and effective response to complex environments. Revealing the interaction networks underlying information flow within these groups is a central challenge. Previous work has modeled interactions between individuals based directly on their relative(More)