کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383599 660827 2013 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Deep sentiment analysis: Mining the causality between personality-value-attitude for analyzing business ads in social media
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Deep sentiment analysis: Mining the causality between personality-value-attitude for analyzing business ads in social media
چکیده انگلیسی


• We propose a model-based method of public health monitoring for solitary elderly people.
• The method generates secondary situational information from activity data gathered at home.
• An experiment was performed with 1236 actual samples.
• The proposed method contributes to improve the quality of health monitoring in terms of accuracy and finding outliers.

IT vendors routinely use social media such as YouTube not only to disseminate their IT product information, but also to acquire customer input efficiently as part of their market research strategies. Customer responses that appear in social media, however, are typically unstructured; thus, a fairly large data set is needed for meaningful analysis. Although identifying customers’ value structures and attitudes may be useful for developing targeted or niche markets, the unstructured and volume-heavy nature of customer data prohibits efficient and economical extraction of such information. Automatic extraction of customer information would be valuable in determining value structure and strength. This paper proposes an intelligent method of estimating causality between user profiles, value structures, and attitudes based on the replies and published content managed by open social network systems such as YouTube. To show the feasibility of the idea proposed in this paper, information richness and agility are used as underlying concepts to create performance measures based on media/information richness theory. The resulting deep sentiment analysis proves to be superior to legacy sentiment analysis tools for estimation of causality among the focal parameters.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 40, Issue 18, 15 December 2013, Pages 7492–7503
نویسندگان
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