Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery

Opinionated text often involves attributes such as authorship and location that influence the sentiments expressed for different aspects. We posit that structural and semantic correspondence is both prevalent in opinionated text, especially when associated with attributes, and crucial in accurately revealing its latent aspect and sentiment structure. However, it is not recognized by existing approaches. We propose Trait, an unsupervised probabilistic model that discovers aspects and sentiments from text and associates them with different attributes. To this end, Trait infers and leverages structural and semantic correspondence using a Markov Random Field. We show empirically that by incorporating attributes explicitly Trait significantly outperforms state-of-the-art baselines both by generating attribute profiles that accord with our intuitions, as shown via visualization, and yielding topics of greater semantic cohesion.Comment: EMNLP 201

Moral Judgments in Narratives on Reddit: Investigating Moral Sparks via Social Commonsense and Linguistic Signals

Given the increasing realism of social interactions online, social media offers an unprecedented avenue to evaluate real-life moral scenarios. We examine posts from Reddit, where authors and commenters share their moral judgments on who is blameworthy. We employ computational techniques to investigate factors influencing moral judgments, including (1) events activating social commonsense and (2) linguistic signals. To this end, we focus on excerpt-which we term moral sparks-from original posts that commenters include to indicate what motivates their moral judgments. By examining over 24,672 posts and 175,988 comments, we find that event-related negative personal traits (e.g., immature and rude) attract attention and stimulate blame, implying a dependent relationship between moral sparks and blameworthiness. Moreover, language that impacts commenters' cognitive processes to depict events and characters enhances the probability of an excerpt become a moral spark, while factual and concrete descriptions tend to inhibit this effect

Cupid:commitments in relational algebra

We propose Cupid, a language for specifying commitments that supports their information-centric aspects, and offers crucial benefits. One, Cupid is first-order, enabling a systematic treatment of commitment instances. Two, Cupid supports features needed for real-world scenarios such as deadlines, nested commitments, and complex event expressions for capturing the lifecycle of commitment instances. Three, Cupid maps to relational database queries and thus provides a set-based semantics for retrieving commitment instances in states such as being violated, discharged, and so on. We prove that Cupid queries are safe. Four, to aid commitment modelers, we propose the notion of well-identified commitments, and finitely violable and finitely expirable commitments. We give syntactic restrictions for obtaining such commitments

Generalized commitment alignment

The interoperability of interacting components means that their expectations of each other remain in agreement. A commitment captures what one agent (its creditor) may expect from another agent (its debtor). Chopra and Singh (C&S) motivate commitment alignment as a meaning-based form of interoperation and show how to ensure alignment among agents despite asynchrony. Although C&S’s approach demonstrates the key strengths of relying on commitment semantics, it suffers from key shortcomings, which limit its applicability in practice. One, C&S do not model commitments properly, causing unacceptable interference between commitments in different transactions. Two, they require that the communication infrastructure guarantee first-in first-out (FIFO) delivery of messages for every agent-agent channel. Three, C&S guarantee alignment only in quiescent states (where no messages are in transit); however, such states may never obtain in enactments of real systems. Our approach retains and enhances C&S’s key strengths and avoids their shortcomings by providing a declarative semantics-based generalized treatment of alignment. Specifically, we (1) motivate a declarative notion of alignment relevant system states termed completeness; (2) prove that it coincides with alignment; and (3) provide the computations by which a system of agents provably progresses toward alignment assuming eventual delivery of messages