THE ASSOCIATION OF SOCIAL ANHEDONIA WITH ROMANTIC RELATIONSHIP PROCESSES

Social anhedonia is a deficiency in the capacity to experience pleasure from social interactions. This study examined the implications of social anhedonia for romantic relationship functioning, including the association of social anhedonia with sentiments towards romantic partners that are central to relationship functioning (satisfaction, commitment, regard, and care), analogous perceptions of the partner’s sentiments, hostile behavior during relationship conflict, and perception of the partner’s hostile behavior. Data were collected from 281 participants who were involved in romantic relationships. Support was found for social anhedonia’s hypothesized negative association with satisfaction, regard, and care, as well as all four perceived partner sentiments. These associations were independent of attachment anxiety and avoidance. Additionally, attachment avoidance mediated social anhedonia’s relationship with commitment. However, no support was found for social anhedonia’s hypothesized positive association with actual and perceived partner hostile behavior. Results suggest that social anhedonia may undermine the functioning of interpersonal relationships.

The emergence of emotions and religious sentiments during the September 11 disaster

Analyzing emotional states under duress or during heightened, life-and-death situations is extremely difficult, especially given the inability of laboratory experiments to replicate the environment and given the inherent biases of post event surveys. This is where natural experiments, such as the pager communications from September 11th can provide the kind of natural experiment emotion researchers have been seeking. We demonstrate that positive and pro-social communications are the first to emerge followed by the slower and lower negative communications. Religious sentiment is the last to emerge, as individual attempt to make sense of event. Additionally we provide a methodological discussion about the preparation and analysis of such natural experiments (the pager message content) and show the importance of using multiple methods to extract the broadest possible understanding.

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Exploiting coherence for the simultaneous discovery of latent facets and associated sentiments

Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.

Dignity and the Challenge to Liberty :Reading Andras Sajo's Constitutional Sentiments

This paper considers debates about the anti-liberal tendencies of the concept of “human dignity”, in particular those conceptions that are “expressivist”. My aim is to examine how far conceptions of dignity are expressivist, and if so what problems the concept of dignity understood in this way poses for liberty. I consider concerns about dignity’s potential illiberality, in particular the potential illiberality of respect-based conceptions of dignity, in the context of Professor András Sajó’s recent writing, illustrating the discussion with examples drawn from recent judicial decisions of the European Court of Human Rights regarding freedom of speech.

Joan Brossa, sentiments i valors en l'art dels infants. 'Joan Brossa, sentimientos y valores en el arte de los niños'.

Resumen de la autora en catalán

Educar en valors ??s educar sentiments morals.

Resumen tomado de la publicaci??n