University of Memphis

About: University of Memphis is a education organization based out in Memphis, Tennessee, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 7710 authors who have published 20082 publications receiving 611618 citations. The organization is also known as: U of M.

Election Night’s Alright for Fighting: The Role of Emotions in Political Participation

Abstract: A large literature has established a persistent association between the skills and resources citizens possess and their likelihood of participating in politics. However, the short-term motivational forces that cause citizens to employ those skills and expend resources in one election but not the next have only recently received attention. Findings in political psychology suggest specific emotions may play an important role in mobilization, but the question of “which emotions play what role?” remains an important area of debate. Drawing on cognitive appraisal theory and the Affective Intelligence model, we predict that anger, more than anxiety or enthusiasm, will mobilize. We find evidence for the distinctive influence of anger in a randomized experiment, a national survey of the 2008 electorate, and in pooled American National Election Studies from 1980 to 2004.

Green marketing strategies: an examination of stakeholders and the opportunities they present

Abstract: As green marketing strategies become increasingly more important to firms adhering to a triple-bottom line performance evaluation, the present research seeks to better understand the role of “green” as a marketing strategy. Through an integration of the marketing, management, and operations literatures, an investigative framework is generated that identifies the various stakeholders potentially impacted through the environmentally friendly efforts of a firm. Specifically, the inter-connected nature of the core business disciplines of marketing, management (both strategy and human resources), and operations are examined as controllable functions within an organization from which strategies can be enacted to affect a firm’s stakeholders. The prior research in these areas is examined to identify potential research opportunities in marketing while also offering a series of representative research questions that can help guide future research in marketing.

MTLD, vocd-D, and HD-D: a validation study of sophisticated approaches to lexical diversity assessment.

Abstract: The main purpose of this study was to examine the validity of the approach to lexical diversity assessment known as the measure of textual lexical diversity (MTLD). The index for this approach is calculated as the mean length of word strings that maintain a criterion level of lexical variation. To validate the MTLD approach, we compared it against the performances of the primary competing indices in the field, which include vocd-D, TTR, Maas, Yule’s K, and an HD-D index derived directly from the hypergeometric distribution function. The comparisons involved assessments of convergent validity, divergent validity, internal validity, and incremental validity. The results of our assessments of these indices across two separate corpora suggest three major findings. First, MTLD performs well with respect to all four types of validity and is, in fact, the only index not found to vary as a function of text length. Second, HD-D is a viable alternative to the vocd-D standard. And third, three of the indices—MTLD, vocd-D (or HD-D), and Maas—appear to capture unique lexical information. We conclude by advising researchers to consider using MTLD, vocd-D (or HD-D), and Maas in their studies, rather than any single index, noting that lexical diversity can be assessed in many ways and each approach may be informative as to the construct under investigation.

Mathematical results on scale‐free random graphs

Abstract: Recently there has been much interest in studying large-scale real-world networks and attempting to model their properties using random graphs. Although the study of real-world networks as graphs goes back some time, recent activity perhaps started with the paper of Watts and Strogatz [55] about the ‘smallworld phenomenon’. Since then the main focus of attention has shifted to the ‘scale-free’ nature of the networks concerned, evidenced by, for example, powerlaw degree distributions. It was quickly observed that the classical models of random graphs introduced by Erdős and Renyi [28] and Gilbert [33] are not appropriate for studying these networks, so many new models have been introduced. The work in this field falls very roughly into the following categories.