5 research outputs found
TwitSong: A current events computer poet and the thorny problem of assessment.
This thesis is driven by the question of how computers can generate poetry, and how that poetry can be evaluated. We survey existing work on computer-generated poetry and interdisciplinary work on how to evaluate this type of computer-generated creative product. We perform experiments illuminating issues in evaluation which are specific to poetry. Finally, we produce and evaluate three versions of our own generative poetry system, TwitSong, which generates poetry based on the news, evaluates the desired qualities of the lines that it chooses, and, in its final form, can make targeted and goal-directed edits to its own work. While TwitSong does not turn out to produce poetry comparable to that of a human, it represents an advancement on the state of the art in its genre of computer-generated poetry, particularly in its ability to edit for qualities like topicality and emotion
Identifying Retweetable Tweets with a Personalized Global Classifier
In this paper we present a method to identify tweets that a user may find
interesting enough to retweet. The method is based on a global, but
personalized classifier, which is trained on data from several users,
represented in terms of user-specific features. Thus, the method is trained on
a sufficient volume of data, while also being able to make personalized
decisions, i.e., the same post received by two different users may lead to
different classification decisions. Experimenting with a collection of approx.\
130K tweets received by 122 journalists, we train a logistic regression
classifier, using a wide variety of features: the content of each tweet, its
novelty, its text similarity to tweets previously posted or retweeted by the
recipient or sender of the tweet, the network influence of the author and
sender, and their past interactions. Our system obtains F1 approx. 0.9 using
only 10 features and 5K training instances.Comment: This is a long paper version of the extended abstract titled "A
Personalized Global Filter To Predict Retweets", of the same authors, which
was published in the 25th ACM UMAP conference in Bratislava, Slovakia, in
July 201