Credell Simeon

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Twitter is a microblogging application, which has gartered much interest in recent years. The main source of attraction is its user-generated content called tweets, that are created daily by users. Tweets are 140-character text messages expressing opinions about different topical issues. They are highly informal, and compact with many different(More)
This paper seeks to identify sentiment and non-sentiment bearing hashtags by combining existing lexical resources. By using a lexicon-based approach, we achieve 86.3% and 94.5% precision in identifying sentiment and non-sentiment hashtags, respectively. Moreover, results obtained from both of our classification models demonstrate that using combined(More)
We present a novel method for classifying hashtag types. Specifically, we apply word segmentation algorithms and lexical resources in order to classify two types of hashtags: those with sentiment information and those without. However, the complex structure of hashtags increases the difficulty of identifying sentiment information. In order to solve this(More)
A recently developed extrapolation method for integrating the equations of motion of mechanical multibody systems is investigated. The inherent parallelism of the extrapolation scheme is used for an implementation on a transputer network. The eeciency of the parallel algorithm is demonstrated at a multibody system which is part of a mechanical printing(More)
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