George Aaron Broadwell

Learn More
The analysis has benefited immensely from discussions with, and (often extensive) comments from, the following colleagues: and Wuppertaler Linguistisches Kolloquium. I owe a particular debt to Alan Prince and Paul Smolensky, for their extremely generous contributions to this work, and to Vieri Samek-Lodovici for his invaluable scrutiny of the manuscript.(More)
This article describes our novel approach to the automated detection and analysis of metaphors in text. We employ robust, quantitative language processing to implement a system prototype combined with sound social science methods for validation. We show results in 4 different languages and discuss how our methods are a significant step forward from(More)
We present in this paper, the application of a novel approach to computational modeling, understanding and detection of social phenomena in online multi-party discourse. A two-tiered approach was developed to detect a collection of social phenomena deployed by participants, such as topic control, task control, disagreement and involvement. We discuss how(More)
In this paper, we describe our experience with collecting and creating an annotated corpus of multi-party online conversations in a chat-room environment. This effort is part of a larger project to develop computational models of social phenomena such as agenda control, influence, and leadership in on-line interactions. Such models will help capturing the(More)
Recent studies in metaphor extraction across several languages (Broadwell et al., 2013; Strzalkowski et al., 2013) have shown that word imageability ratings are highly correlated with the presence of metaphors in text. Information about imageability of words can be obtained from the MRC Psycholinguistic Database (MRCPD) for English words and Léxico(More)
In this paper, we describe a novel approach to computational modeling and understanding of social and cultural phenomena in multi-party dialogues. We developed a two-tier approach in which we first detect and classify certain social language uses, including topic control, disagreement, and involvement, that serve as first order models from which presence(More)
In this article, we present a novel approach towards the detection and modeling of complex social phenomena in multi-party discourse, including leadership, influence, pursuit of power and group cohesion. We have developed a two-tier approach that relies on observable and computable linguistic features of conversational text to make predictions about(More)
This article describes a novel approach to automated determination of affect associated with metaphorical language. Affect in language is understood to mean the attitude toward a topic that a writer attempts to convey to the reader by using a particular metaphor. This affect, which we will classify as positive, negative or neutral with various degrees of(More)
In this article, we present details about our ongoing work towards building a repository of Linguistic and Conceptual Metaphors. This resource is being developed as part of our research effort into the large-scale detection of metaphors from unrestricted text. We have stored a large amount of automatically extracted metaphors in American English, Mexican(More)