Golbeck [10] Twitter Google 4 2. [3], [4] [5], [6] SPAM k-anonymity [7] k-anonymity Leavitt [8] Ikeda [9] Golbeck Twitter [10] c 2013 Information Proc
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1 1,a) , Web 4 Study of Methods to Diminish Spoilers of Sports Match: Potential of a Novel Concept Information Clouding Satoshi Nakamura 1,a) Takanori Komatsu 1 Received: June 27, 2012, Accepted: January 11, 2013 Abstract: Seeing the final score of a sports match on the Web often spoils the pleasure of a user who is waiting to watch a recording of this match on TV. This paper proposes four information clouding methods to block spoiling information, and describes implementation of a system using these methods as a browser extension. We then experimentally investigate the usefulness of the methods, taking into account their differences, differences in the variety of content, and differences in the user s interest in sports. Keywords: information clouding, spoilers, sports, web 1. glee Twitter *1 1 Department of Frontier Media Science, School of Interdisciplinary Mathematical Sciences, Meiji University, Nakano, Tokyo , Japan a) satoshi@snakamura.org *1 aspx c 2013 Information Processing Society of Japan 1402
2 Golbeck [10] Twitter Google 4 2. [3], [4] [5], [6] SPAM k-anonymity [7] k-anonymity Leavitt [8] Ikeda [9] Golbeck Twitter [10] c 2013 Information Processing Society of Japan 1403
3 Golbeck 100% 100% 3. [1] ToDo Wikipedia MeCab API 4.2 CGI c 2013 Information Processing Society of Japan 1404
![[2] 1 1 4 73 154 F1 4.3 4 2 Fig.](/docs-images/91/106343584/images/4-1.jpg "2 Invisible method. 3 Fig.")
4 1 Fig. 1 Examples of regular expression. [2] F Fig. 2 Invisible method. 3 Fig. 3 Censored method. 4.4 Mozilla Firefox JavaScript XUL c 2013 Information Processing Society of Japan 1405
5 5. 4 Fig. 4 Increasing method Web 5 Fig. 5 Inverse method. 6 Fig. 6 A screen shot of our system. 5 6 UI UI WBC 4 URL c 2013 Information Processing Society of Japan 1406
6 1 5 7 Table 1 Questionnaire for each method of information clouding / / / 4 / / / 2 / F(3, 57) = 0.97 n.s. 2 F(3, 57) = 1.24 n.s. 3 > F(1, 57) = 5.04 p <.05 c 2013 Information Processing Society of Japan 1407
7 情報処理学会論文誌 Vol.54 No (Apr. 2013) 図 7 表現手法要因およびスポーツ興味要因の二要因混合計画の分散分析結果 項目間の実線 は 5%水準での有意差を示している Fig. 7 Results of mixed ANOVA among method and preference factors. 図 8 コンテンツ要因およびスポーツ興味要因二要因混合計画の分散分析結果 Fig. 8 Results of mixed ANOVA among contents and preference factors. 表 2 表現手法要因 スポーツ興味要因の二要因混合計画の統計量 Table 2 F-statistical of mixed ANOVA among method and preference factors. 図 9 手法要因ごとの正解数 Fig. 9 Spoiled numbers in each method. テニス 質問 3 および 7 の表現手法要因のみに有意差 因間で同じ表現手法のペアを比較およびスポーツ興味要因 が観察された 質問 3 F(3, 57) = p <.01 質 内でそれぞれの表現手法のペアを比較する直接確率計算 問 7 F(3, 57) = 4.19 p <.05 を行ったところ いずれのペアについても有意差が観察さ これらの結果より サッカー男子は他のコンテンツと比 れなかったため 表現手法要因およびスポーツ興味要因は べて質問 1 および 2 の非表示 墨塗り手法に対する回答傾 ユーザがネタバレ情報を理解したか否かという機能的な側 向が異なっていることが明らかになった また 他のコン 面に関しては特に影響を与えていなかったことが確認さ テンツと比較すると テニスに関しては表現手法要因の影 れた 響が小さかったことが明らかとなった コンテンツ要因およびスポーツ興味要因の影響 参加者が実際にネタバレに気づいた数を表現手法要因ご 各質問項目に関して 二要因混合計画 独立変数その 1 とにまとめた 正解数 を図 9 に示す スポーツ興味要 コンテンツ要因 被験者内配置 4 水準 独立変数その 2 c 2013 Information Processing Society of Japan 1408
8 3 Table 3 F-statistics of mixed ANOVA among contents and preference factors. 10 Fig. 10 Spoiled numbers in each content > 1 F(1, 57) = 7.21 p <.05 2 F(1, 57) = 4.20 p <.05 6 F(1, 57) = 6.22 p < F(3, 57) = 3.15 p <.05 5 F(3, 57) = 4.63 p <.05 1 F(3, 57) = 3.29 p <.05 3 F(3, 57) = 3.06 p < Q1 Q2 Q6 1 4 c 2013 Information Processing Society of Japan 1409
9 Yahoo! mixi F1 WeData *2 Web Web Ikeda [9] Twitter Twitter Twitter *2 c 2013 Information Processing Society of Japan 1410
![orz 2 Twitter Goooaaaalllllll!!! Brody [11] Twitter Ajax Flash 7. 4 A 23680006 [1] Nakamura, S. and Tanaka, K.: Temporal Filtering System for Reducing the Risk of Spoiling a User s Enjoyment, Proc.](/docs-images/91/106343584/images/10-0.jpg "IUI 2007, pp.345 348 (2007). [2] Cai, D., Yu, S., Wen, J.R. and Ma, W.Y.: VIPS: A Vision-based Page Segmentation Algorithm, Microsoft Technical Report (2003-79) (2003). [3] Vol.19, No.3, pp.")
10 orz 2 Twitter Goooaaaalllllll!!! Brody [11] Twitter Ajax Flash 7. 4 A [1] Nakamura, S. and Tanaka, K.: Temporal Filtering System for Reducing the Risk of Spoiling a User s Enjoyment, Proc. IUI 2007, pp (2007). [2] Cai, D., Yu, S., Wen, J.R. and Ma, W.Y.: VIPS: A Vision-based Page Segmentation Algorithm, Microsoft Technical Report ( ) (2003). [3] Vol.19, No.3, pp (2004). [4] Riecken, D. guest ed.: Personalized views of personalization (special edition), Comm. ACM, Vol.43, No.8 (2008). [5] DigitalArts Inc.: i-filter, available from daj.co.jp/. [6] Sahami, M., Dumais, S., Heckerman, D. and Horvitz, E.M.: A Bayesian Approach to Filtering Junk , AAAI Technical Report WS (1998). [7] Sweeney, L.: Achieving k-anonymity privacy protection using generalization and suppression, International Journal on Uncertainty, Fuzziness and Knowledgebased Systems, Vol.10, No.5, pp (2002). [8] Leavitt, J.D. and Christenfeld, N.J.S.: Story Spoilers Don t Spoil Stories, Psychological Science (Aug. 2011). [9] Ikeda, K., Hijikata, Y. and Nishida, S.: Proposal of Deleting Plots from the Reviews to the Items with Stories, Proc. SNSMW 10, CDROM (2010). [10] Golbeck, J.: The Twitter Mute Button: A Web Filtering Challenge, Proc ACM Annual Conference on Human Factors in Computing Systems, pp (2012). [11] Brody, S. and Diakopoulos, N.: Cooooooooooooooollll llllllllll!!!!!!!!!!!!!!: Using word lengthening to detect sentiment in microblogs, Proc. Conference on Empirical Methods in Natural Language Processing, pp (2011) c 2013 Information Processing Society of Japan 1411
11 ACM c 2013 Information Processing Society of Japan 1412
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