Biographically Relevant Tweets – a New Dataset, Linguistic Analysis and Classification Experiments
We present a new dataset comprising tweets for the novel task of detecting biographically relevant utterances. Biographically relevant utterances are all those utterances that reveal some persistent and non-trivial information about the author of a tweet, e.g. habits, (dis)likes, family status, physical appearance, employment information, health issues etc. Unlike previous research we do not restrict biographical relevance to a small fixed set of pre-defined relations. Next to classification experiments employing state-of-the-art classifiers to establish strong baselines for future work, we carry out a linguistic analysis that compares the predictiveness of various high-level features. We also show that the task is different from established tasks, such as aspectual classification or sentiment analysis.
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