Many types of features were employed, including word length, sentence length, paragraph length, document length, sentence complexity, punctuation and capitalization, cognates, dependency parses, topic models, word suffixes, collocations, function word ngrams, skip-grams, word networks, Tree Substitution Grammars, string kernels, cohesion, and passive constructions (Abu-Jbara et al., 2013;Li, 2013;Brooke and Hirst, 2013;Cimino et al., 2013;Daudaravicius, 2013;Goutte et al., 2013;Henderson et al., 2013;Hladka et al., 2013;Bykh et al., 2013;Lahiri and Mihalcea, 2013;Lynum, 2013;Malmasi et al., 2013;Mizumoto et al., 2013;Nicolai et al., 2013;Popescu and Ionescu, 2013;Swanson, 2013;Tsvetkov et al., 2013).
word n-gram features appear to be particularly effective, as they were used by the most competitive teams, including the one that achieved the highest overall accuracy (Jarvis et al., 2013).