Causal Inference in Graph-Text Constellations:Designing Verbally Annotated Graphs

作     者：Christopher Habel Cengiz Acartürk 

作者机构：Department of InformaticsUniversity of Hamburg Informatics InstituteMiddle East Technical University 

基　　金：Supported in part by DFG(German Science Foundation) in ITRG1247‘Cross-modal Interaction in Natural and Artificial Cognitive Systems’(CI-NACS) 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2011年第16卷第1期

页      码：7-12页

摘      要：Multimodal documents combining language and graphs are wide-spread in print media as well as in electronic media. One of the most important tasks to be solved in comprehending graph-text combinations is construction of causal chains among the meaning entities provided by modalities. In this study we focus on the role of annotation position and shape of graph lines in simple line graphs on causal attributions concerning the event presented by the annotation and the processes （i.e, increases and decreases） and states （no-changes） in the domain value of the graphs presented by the process-lines and state-lines. Based on the experimental investigation of readers＇ inferences under different conditions, guidelines for the design of multimodal documents including text and statistical information graphics are suggested. One suggestion is that the position and the number of verbal annotations should be selected appropriately, another is that the graph line smoothing should be done cautiously.

主 题 词：causal inference multimodal comprehension human computer interaction 

学科分类：1305[艺术学-设计学类] 13[艺术学] 

核心收录：

D　O　I：10.1016/S1007-0214(11)70002-5

馆 藏 号：203384680...