|Author||Jensen, Matthew L ♦ Burgoon, Judee K ♦ Nunamaker, Jay F|
|Source||ACM Digital Library|
|Publisher||Association for Computing Machinery (ACM)|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||Credibility assessment ♦ Deception detection ♦ Decision-aids ♦ Human-computer interaction ♦ Information veracity ♦ Kinesics ♦ Linguistics|
|Abstract||One of the most pernicious threats to information quality comes through perpetration of deception by information suppliers. Deception undermines many critical dimensions of information quality, such as accuracy, completeness, and believability. Despite this threat, information gatherers are ill equipped to assess the credibility of information suppliers. This work presents a prototype system that examines messages gathered during direct, face-to-face information gathering. The system unobtrusively identifies kinesic and linguistic features that may indicate deception in information suppliers’ messages. System use was found to significantly improve assessment ability in between-subjects and within-subjects tests. The improved ability to accurately assess credibility during face-to-face interactions should yield higher information quality.|
|Age Range||18 to 22 years ♦ above 22 year|
|Education Level||UG and PG|
|Learning Resource Type||Article|
|Publisher Place||New York|
|Journal||Journal of Data and Information Quality (JDIQ)|
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