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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/71484

    Title: 微網誌使用者週中日的發文情緒對產品推薦效果之影響;The Impact of User Sentiment aroused by The-Day-Of-The-Week on the Recommendation Effectiveness in Microblog
    Authors: 翁詩韻;YUN,ONG SHI
    Contributors: 企業管理學系
    Keywords: 社群網站;微網誌;情緒字詞;週中日;social network;microblog;sentiment word;Plurk;the-day-of-the-week
    Date: 2016-06-29
    Issue Date: 2016-10-13 13:07:35 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 自社群網站興起後,在虛擬世界交流的人數驟增。其中的微網誌平台因使用者發文簡短、方便且容易吸引關注者回應,而累積了龐大的資料量。然而如何利用這些含有情緒成分的大量訊息,並結合人們在一週中的不同日子表現的不同情緒,有效推薦可能投合他們所需產品或服務的相關研究付之闕如。
    ;With the rise of social networking sites, microblogging has become an increasingly popular platform for users to post their views and comments online due to the ease of posting and replying. This generated an abundance of sentiment database which could be used to study the-day-of-the-week sentiment patterns of users. However, previous studies never focus on this phenomenon to recommend products or services.
    In this study, we adopted sentiment database to extract sentiment expressions from the posted Plurk messages to investigate whether there are sentiment fluctuations in the days of a week and if there are opportunities to use the-day-of-the-week sentiment patterns to maximize the effectiveness of sentiment-based product recommendation.
    The experimental results showed that users’ posts are significantly strong negative on Monday and strong positive on Friday, Saturday, and Sunday. We speculate that the recommended products with positive sentiment words were more effective during Monday and Saturday because of the approach-avoidance motivation. People would usually have negative sentiment after 5 days continuous work during Friday working hours, so that recommended products with negative sentiment words are more effective. Whereas on Friday night the positive sentiment increased after off duty, and caused the recommendation products with positive sentiment words more effective. Negative sentiment on Sunday due to the coming blue Monday may cause negative sentiment recommendations more effective.
    This study is helpful for marketers to employ sentiment-based recommendation and determine how to focus their limited financial resources to appeal to the most likely interested in customers based on their sentiment patterns and thus maximize sales revenue.
    Appears in Collections:[企業管理研究所] 博碩士論文

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