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Association: Name: International Communication Association URL: http://www.icahdq.org
Citation: URL: http://www.allacademic.com/meta/p92381_index.html Direct Link: HTML Code:

Klein, Alyssa. and Humphreys, Lee. "Measuring Online Social Support: Can Computer-Based Text Analysis Approximate Burleson’s Person-Centered Hierarchy?" Paper presented at the annual meeting of the International Communication Association, Dresden International Congress Centre, Dresden, Germany, <Not Available>. 2009-05-25 <http://www.allacademic.com/meta/p92381_index.html>

Klein, A. C. and Humphreys, L. M. "Measuring Online Social Support: Can Computer-Based Text Analysis Approximate Burleson’s Person-Centered Hierarchy?" Paper presented at the annual meeting of the International Communication Association, Dresden International Congress Centre, Dresden, Germany Online <PDF>. 2009-05-25 from http://www.allacademic.com/meta/p92381_index.html

Publication Type: Conference Paper/Unpublished Manuscript Abstract: Social support has been linked to improved physical and mental well-being, especially for those facing serious illness. However, little is known about the mechanism of these effects. One approach to understanding supportive communication has demonstrated that highly person-centered messages, which explicitly acknowledge and elaborate the feelings of a distressed individual, are perceived as being more helpful, supportive, and involved, and therefore the most effective at comforting. Classifying messages according to degree of person-centeredness requires trained coders and significant amounts of time. The purpose of the current study is to determine whether a computerized linguistic analysis tool can predict hand-scored person-centeredness, and also more specifically, to identify which linguistic categories are the best explanatory variables. A body of 334 messages drawn from online support groups for breast cancer patients was analyzed firstly by independent coders to assess person-centeredness, and secondly by a computerized linguistic analysis program to evaluate the messages across emotional and other linguistic dimensions. Regression models were used to test the extent to which linguistic dimensions are able to predict person-centeredness. Results indicate that word count is the strongest predictor of hierarchy, but that highly person-centered messages are also characterized by words expressing emotion and certainty.

What Women Know and Feel about Social Support that Men Don't: Two Tests of a Dual-Process Approach to Explaining Sex Differences in Responses to Supportive Messages

Person-organization Congruence and the Maintenance of Group-Based Social Hierarchy: A Social Dominance Perspective

Validating the Person-Centered Hierarchy: Does Person-Centeredness Account for Perceived Effectiveness of Breast Cancer Support Group Messages?

I Know How You Feel: A Person-Centered Approach to Supportive Messages in Online Breast Cancer Groups