An annotation scheme for citation function

We study the interplay of the discourse structure of a scientific argument with formal citations. One subproblem of this is to classify academic citations in scientific articles according to their rhetorical function, e.g., as a rival approach, as a part of the solution, or as a flawed approach that justifies the current research. Here, we introduce our annotation scheme with 12 categories, and present an agreement study

Effects on Inter-Personal Memory of Dancing in Time with Others.

We report an experiment investigating whether dancing to the same music enhances recall of person-related memory targets. The experiment used 40 dancers (all of whom were unaware of the experiment's aim), two-channel silent-disco radio headphones, a marked-up dance floor, two types of music, and memory targets (sash colors and symbols). In each trial, 10 dancers wore radio headphones and one of four different colored sashes, half of which carried cat symbols. Using silent-disco technology, one type of music was surreptitiously transmitted to half the dancers, while music at a different tempo was transmitted to the remaining dancers. Pre-experiment, the dancers' faces were photographed. Post-experiment, each dancer was presented with the photographs of the other dancers and asked to recall their memory targets. Results showed that same-music dancing significantly enhanced memory for sash color and sash symbol. Our findings are discussed in light of recent eye-movement research that showed significantly increased gaze durations for people observing music-dance synchrony versus music-dance asynchrony, and in relation to current literature on interpersonal entrainment, group cohesion, and social bonding

An Information-Theoretical Method for Comparing Completions of Contrapunctus XIV from Bach’s Art of Fugue

The unfinished final Contrapunctus from Bach’s posthumously-published Kunst der Fuge has received several dozen completions over the past century. Although the majority of these have been published and recorded, none has yet established themselves as the leading solution among performers, and this may have more to do with their perceived ‘Bach-ness’ than the undoubted contrapuntal skill and ingenuity that they each demonstrate. This study uses an established information-theoretical method drawn from mathematics to explore the extent to which it is possible to ‘measure’ the similarity of these reconstructions to the original, and so determine which are closest to the musical lines of Bach’s existing opening of Contrapunctus XIV

Automatic Classification of Citation Function

Citation function is defined as the author’s reason for citing a given paper (e.g. acknowledgement of the use of the cited method). The automatic recognition of the rhetorical function of citations in scientific text has many applications, from improvement of impact factor calculations to text summarisation and more informative citation indexers. We show that our annotation scheme for citation function is reliable, and present a supervised machine learning framework to automatically classify citation function, using both shallow and linguistically-inspired features. We find, amongst other things, a strong relationship between citation function and sentiment classification

Every Track You Take: Analysing the Dynamics of Song and Genre Reception Through Music Downloading

Using a music-download database provided by the Nokia Corporation, this paper explores three primary questions: (1) Do different musical genres create different patterns of downloading? (2) Do different countries download a particular song in different ways? And (3) how do different events affect downloading? Question (1) is studied in relation to representative songs from the pop, rap and rock genres, and reveals rock to be significantly different from pop and rap in a number of key respects. Question (2) investigates the downloading patterns of a mainstream pop song in Brazil, Germany, Italy, and Mexico. Using Kolmogorov-Smirnoff tests to compare the countries’ download distributions, Brazil is found to be substantially dissimilar to the other countries. And Question (3) is explored with respect to types of event, the first "musical" (Adele's Grammy Awards triumph in February 2012), and the second "extra-musical" (the death of Michael Jackson in June 2009). The extra-musical event is found to have had a far greater effect on downloading patterns than the musical event. The findings are discussed in relation to various factors, including musical genres, the music industry, social media, and globalisation.   À l’aide d’une base de données de téléchargement de musique fournie par Nokia Corporation, cet essai explore trois questions principales : (1) Est-ce que différents genres de musique créent différents modèles de téléchargement? (2) Est-ce qu’une chanson en particulier est téléchargée de différentes façons dans différents pays ? Et (3) comment différents événements affectent-ils le téléchargement ? La question (1) est étudiée relativement à des chansons représentatives des genres pop, rap et rock, et révèle que le rock est sensiblement différent des musiques pop et rap à bien des égards. La question (2) examine les modèles de téléchargement d’une chanson pop au Brésil, en Allemagne, en Italie et au Mexique. Faisant appel aux tests de Kolmogorov-Smirnov pour comparer les distributions de téléchargement de ces pays, on a découvert que le Brésil est sensiblement différent des autres pays. Et à la question (3), on explore les types d’événements, premièrement un événement "musical" (le triomphe d’Adele lors des Grammy Awards en février 2012), et deuxièmement un événement "extra-musical" (la mort de Michael Jackson en juin 2009). On a constaté que l’événement extra-musical a eu un effet beaucoup plus important sur les modèles de téléchargement que l’événement musical. Les constatations font l’objet de discussions relativement aux divers facteurs, y compris les genres musicaux, l’industrie de la musique, les médias sociaux et la mondialisation

From Human Evaluation to Automatic Selection of Good Translations

In this paper we describe a machine learning method tailored to overcome the difficulty of selecting and putting together translated segments in the Verbmobil system. We use off line human feedback to determine an optimized confidence rescaling scheme for the confidence values provided by four independent and competing translation paths in Verbmobil. 1