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• {"link"=>{"url"=>"http://www.citeulike.org/user/shuaiyizhang/article/13414263"}, "post_time"=>"2014-10-31 03:19:52", "tag"=>["big", "data"], "linkout"=>{"type"=>"DOI", "url"=>"http://dx.doi.org/10.1371/journal.pone.0071226"}, "username"=>"shuaiyizhang", "article_id"=>"13414263"}

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{"title"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data", "type"=>"journal", "authors"=>[{"first_name"=>"Márton", "last_name"=>"Mestyán", "scopus_author_id"=>"55830068600"}, {"first_name"=>"Taha", "last_name"=>"Yasseri", "scopus_author_id"=>"26531952500"}, {"first_name"=>"János", "last_name"=>"Kertész", "scopus_author_id"=>"35473453300"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84882719407", "doi"=>"10.1371/journal.pone.0071226", "sgr"=>"84882719407", "arxiv"=>"1211.0970", "isbn"=>"1932-6203", "pmid"=>"23990938", "issn"=>"19326203", "pui"=>"369619800"}, "id"=>"202585e2-409f-346d-be8f-81adeeccd4cd", "abstract"=>"Use of socially generated “big data” to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between “real time monitoring” and “early predicting” remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.", "link"=>"http://www.mendeley.com/research/early-prediction-movie-box-office-success-based-wikipedia-activity-big-data", "reader_count"=>222, "reader_count_by_academic_status"=>{"Unspecified"=>6, "Professor > Associate Professor"=>11, "Researcher"=>32, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>61, "Student > Postgraduate"=>7, "Student > Master"=>53, "Other"=>3, "Student > Bachelor"=>24, "Lecturer"=>6, "Professor"=>9}, "reader_count_by_user_role"=>{"Unspecified"=>6, "Professor > Associate Professor"=>11, "Researcher"=>32, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>61, "Student > Postgraduate"=>7, "Student > Master"=>53, "Other"=>3, "Student > Bachelor"=>24, "Lecturer"=>6, "Professor"=>9}, "reader_count_by_subject_area"=>{"Unspecified"=>12, "Agricultural and Biological Sciences"=>4, "Arts and Humanities"=>5, "Philosophy"=>1, "Business, Management and Accounting"=>26, "Chemistry"=>2, "Computer Science"=>80, "Decision Sciences"=>1, "Earth and Planetary Sciences"=>3, "Economics, Econometrics and Finance"=>10, "Engineering"=>16, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>6, "Medicine and Dentistry"=>1, "Design"=>1, "Physics and Astronomy"=>6, "Psychology"=>6, "Social Sciences"=>40}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>40}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Psychology"=>{"Psychology"=>6}, "Mathematics"=>{"Mathematics"=>6}, "Unspecified"=>{"Unspecified"=>12}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>5}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>16}, "Chemistry"=>{"Chemistry"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>3}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>10}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>80}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>26}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Romania"=>1, "United States"=>4, "United Kingdom"=>2, "Portugal"=>1, "Switzerland"=>1, "Netherlands"=>1, "Korea (South)"=>1, "Brazil"=>1, "Italy"=>1, "Israel"=>1, "Slovakia"=>1, "Australia"=>1, "France"=>1, "Germany"=>3}, "group_count"=>16}

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Article Coverage Curated

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Journal Comments | Further Information

• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/e064d698-e102-4db3-a00f-7e84c77e03ec", "title"=>"Media Coverage of this Article", "body"=>"Wikipedia buzz predicts blockbuster movies' takings weeks before release\n8 November 2012 The Guardian \nhttp://www.theguardian.com/science/2012/nov/08/wikipedia-buzz-blockbuster-movies-takings\n\nNow Wikipedia used to predict movie box office revenues\n7 November 2012 MIT Technology Review\nhttp://www.technologyreview.com/view/507076/now-wikipedia-used-to-predict-movie-box-office-revenues/\n\nWikipedia data could be used to predict box office success\n7 November 2012 Wired UK\nhttp://www.wired.co.uk/news/archive/2012-11/07/wikipedia-box-office-predictions\n\nUsing Wikipedia to predict the box office of a movie\n9 November 2012 Forbes\nhttp://www.forbes.com/sites/timworstall/2012/11/09/using-wikipedia-to-predict-the-box-office-of-a-movie/\n\nWikipedia data 'can predict success of films'\n9 November 2012 The Telegraph\nhttp://www.telegraph.co.uk/technology/wikipedia/9666484/Wikipedia-data-can-predict-success-of-films.html\n\nWikipedia Pages Predict Movie Success, Hungarian Scientists Claim\n9 November 2012 Huffington Post\nhttp://www.huffingtonpost.com/2012/11/08/wikipedia-movie_n_2094679.html\n\nWikipedia soll Erfolg von Filmen vorhersagen\n9 November 2012 Spiegel Online Kultur\nhttp://www.spiegel.de/kultur/kino/studie-wikipedia-soll-erfolg-von-kinofilmen-vorhersagen-a-866290.html\n\nWikipedia Can Forsee Box Office Success Ahead of Release, say Researchers\n11 November 2012 International Business Times (India)\nhttp://www.ibtimes.co.in/articles/403752/20121111/wikipedia-predict-box-office-hits-taha-yasseri.htm\n\nCan Wikipedia predict a box office hit?\n9 November 2012 Salon\nhttp://www.salon.com/2012/11/09/can_wikipedia_predict_a_box_office_hit/singleton/\n\nHow Wikipedia can spot a box office smash a month before it is released\n9 November 2012 Daily Mail\nhttp://www.dailymail.co.uk/sciencetech/article-2230406/How-Wikipedia-spot-box-office-smash-month-released.html\n\nUn modèle mathématique reposant sur Wikipédia pourrait prévoir les futurs films à succès au box-office\n9 November 2012 Huffington Post (France)\nhttp://www.huffingtonpost.fr/2012/11/09/wikipedia-box-office-prevision-blockbuser-videos_n_2098979.html\n\nFilm Industry to Turn to Wikipedia for Predictive Analytics?\n12 November 2012 Datanami\nhttp://www.datanami.com/datanami/2012-11-12/film_industry_to_turn_to_wikipedia_for_predictive_analytics_.html\n\n", "isRemoved"=>false, "created"=>"2013-08-22T07:58:41Z", "lastModified"=>"2013-08-22T07:58:41Z", "creator"=>{"userId"=>"115789"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"I'm one of the authors. "}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>3, "mostRecentActivity"=>"2013-09-04T18:03:56Z", "replies"=>[{"type"=>"REPLY", "parentID"=>70711, "annotationUri"=>"info:doi/10.1371/reply/f6b03475-1945-49fb-8fa5-e41c9e8f4319", "title"=>"More Coverage", "body"=>"Wikipedia Can Predict Box-Office Hits\nLive Science August 21, 2013\nhttp://www.livescience.com/39075-wikipedia-blockbuster-prediction.html\n\nWikipedia Data Predicts Movie Blockbusters (Infographic)\nLive Science August 21, 2013\nhttp://www.livescience.com/39063-wikipedia-data-predicts-movie-blockbusters-infographic.html", "isRemoved"=>false, "created"=>"2013-08-22T21:05:45Z", "lastModified"=>"2013-08-22T21:05:45Z", "creator"=>{"userId"=>"115789"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"I am an author of the article."}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>2, "mostRecentActivity"=>"2013-09-04T18:03:56Z", "replies"=>[{"type"=>"REPLY", "parentID"=>70757, "annotationUri"=>"info:doi/10.1371/reply/5cd31453-2d57-46fb-9501-289b32d3ef81", "title"=>"Media coverage of this article", "body"=>"The following article represents some of the media coverage that has occurred for this paper:\n\nPublication: LiveScience \nTitle: “Wikipedia Data Predicts Movie Blockbusters (Infographic) | LiveScience”\nhttp://www.livescience.com/39063-wikipedia-data-predicts-movie-blockbusters-infographic.html\n\nPublication: Motherboard \nTitle: “Wikipedia Can Predict Box Office Flops | Motherboard”\nhttp://motherboard.vice.com/blog/wikipedia-can-predict-box-office-flops\n\nIf you see any additional coverage of this paper in the press or blogosphere, please reply to this thread and add the link to the article. \n", "isRemoved"=>false, "created"=>"2013-08-23T18:07:53Z", "lastModified"=>"2013-08-23T18:07:53Z", "creator"=>{"userId"=>"80539"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"PLOS ONE Staff"}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>1, "mostRecentActivity"=>"2013-09-04T18:03:56Z", "replies"=>[{"type"=>"REPLY", "parentID"=>70885, "annotationUri"=>"info:doi/10.1371/reply/41f06ade-fbab-42d7-8338-ef1e5d4798de", "title"=>" Media coverage of this article", "body"=>"The following article represents some of the media coverage that has occurred for this paper:\n\nPublication: EveryONE PLOS ONE Community Blog \nTitle: “Predicting Movie Box Office Success Using Wikipedia | EveryONE”\nhttp://blogs.plos.org/everyone/2013/08/23/predicting-movie-box-office-success-using-wikipedia/\n\nPublication: Motherboard \nTitle: “Wikipedia Can Predict Box Office Flops | Motherboard”\nhttp://motherboard.vice.com/blog/wikipedia-can-predict-box-office-flops\n\nIf you see any additional coverage of this paper in the press or blogosphere, please reply to this thread and add the link to the article. \n", "isRemoved"=>false, "created"=>"2013-09-04T18:03:56Z", "lastModified"=>"2013-09-04T18:03:56Z", "creator"=>{"userId"=>"80539"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"PLOS ONE Staff"}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2013-09-04T18:03:56Z", "replies"=>[]}]}]}]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/2141bf4d-dbe5-4a76-a2ec-fd916900cb4d", "title"=>"Correct e-mail address", "body"=>"The correct e-mail address of the corresponding author is: taha.yasseri@oii.ox.ac.uk\n ", "isRemoved"=>false, "created"=>"2013-08-22T08:53:43Z", "lastModified"=>"2013-08-22T08:53:43Z", "creator"=>{"userId"=>"115789"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"I am the corresponding author."}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2013-08-22T08:53:43Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/dc158f3c-c4b5-4058-ae74-031fede99fb8", "title"=>"Using # of theatres in the prediction model", "body"=>"Dear Sirs,\n\nI really enjoyed your article and it has some very informative comparisons to previous work and new ideas as well. However, having a bit of experience in the movie industry, the number of theatres, or theatre screens a movie is going to play in is not really something you would know in advance in general, so it feels like using that value in the prediction model is a bit of a cheat here as the final box office number is likely to be highly dependent on it.\n\nNot to take anything away from the work anyway, but just maybe worth a note if someone were to try and apply the model in real world.\n\nRegards,\nMartin", "isRemoved"=>false, "created"=>"2015-03-27T14:20:09Z", "lastModified"=>"2015-03-27T14:20:09Z", "creator"=>{"userId"=>"502596"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>1, "mostRecentActivity"=>"2015-04-07T23:38:39Z", "replies"=>[{"type"=>"REPLY", "parentID"=>85873, "annotationUri"=>"info:doi/10.1371/reply/64a303c7-0d48-43e0-8750-3996b9ce855d", "title"=>"RE: Using # of theatres in the prediction model", "body"=>"Dear Martin, \n\nThank you very much for your comment.\nYou're absolutely right about the availability of the data on the number of theatres assigned to each movie. We wished that the readers would notice the hypothetical framework of our research. However, regarding your comment \"final box office number is likely to be highly dependent on it.\", this is something that we calculated and reported in the paper (see the grey dashed lines in fig. 2). We also showed that the presented model outperforms a model solely based on the number of theatres (fig 3.).\n\nThank you very much again for your useful comment.\nBest,\nTaha ", "isRemoved"=>false, "created"=>"2015-04-07T23:38:39Z", "lastModified"=>"2015-04-07T23:38:39Z", "creator"=>{"userId"=>"115789"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>true, "body"=>"Corresponding author. "}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0071226", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2015-04-07T23:38:39Z", "replies"=>[]}]}

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• {"id"=>"370295521191022593", "text"=>"our @PLoSONE paper on \"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data\" is out http://t.co/nULtiLm1xg", "created_at"=>"2013-08-21T21:25:06Z", "user"=>"TahaYasseri", "user_name"=>"Taha Yasseri", "user_profile_image"=>"http://a0.twimg.com/profile_images/2094692556/met_normal.jpg"}
• {"id"=>"370309262574374912", "text"=>"@nephondemand http://t.co/rSq28sitZo", "created_at"=>"2013-08-21T22:19:42Z", "user"=>"PLOSONE", "user_name"=>"PLOS ONE", "user_profile_image"=>"http://a0.twimg.com/profile_images/2429958559/mzjl6as5u2m09r2erof6_normal.jpeg"}
• {"id"=>"370309666976174081", "text"=>"@nephondemand @PLOSONE http://t.co/u9z0A30qnF", "created_at"=>"2013-08-21T22:21:19Z", "user"=>"TahaYasseri", "user_name"=>"Taha Yasseri", "user_profile_image"=>"http://a0.twimg.com/profile_images/2094692556/met_normal.jpg"}
• {"id"=>"370317148993765376", "text"=>"あれ？プラスワンに掲載？おかしいな。どこかで見たはずなのに…。Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/MJYy10yoaT", "created_at"=>"2013-08-21T22:51:03Z", "user"=>"uranus_2", "user_name"=>"マーキュリー２世", "user_profile_image"=>"http://a0.twimg.com/sticky/default_profile_images/default_profile_5_normal.png"}
• {"id"=>"370372603673731074", "text"=>"Movie success can be predicted before release by analysing activity levels on Wikipedia, say European researchers http://t.co/izViDz0xaO", "created_at"=>"2013-08-22T02:31:24Z", "user"=>"AusSMC", "user_name"=>"Au Science Media Ctr", "user_profile_image"=>"http://a0.twimg.com/profile_images/700391083/twitter_logo_normal.jpg"}
• {"id"=>"370435610676183041", "text"=>"Interesting... Early prediction of movie box office success based on Wikipedia activity big data http://t.co/Pvq4QQ4Wp1", "created_at"=>"2013-08-22T06:41:46Z", "user"=>"SCPHRP", "user_name"=>"SCPHRP ", "user_profile_image"=>"http://a0.twimg.com/profile_images/2759122495/f58895030982206e9b626c57174a6451_normal.jpeg"}
• {"id"=>"370467329148063744", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data:\nhttp://t.co/aL21j6IplT", "created_at"=>"2013-08-22T08:47:48Z", "user"=>"FarzanehKaveh9", "user_name"=>"Farzaneh Kaveh", "user_profile_image"=>"http://a0.twimg.com/profile_images/3056647062/a708095e10f572f679e5ae990f91904b_normal.jpeg"}
• {"id"=>"370494442156728320", "text"=>"RT @SCPHRP: Interesting... Early prediction of movie box office success based on Wikipedia activity big data http://t.co/Pvq4QQ4Wp1", "created_at"=>"2013-08-22T10:35:33Z", "user"=>"LizHoffmanbmc", "user_name"=>"Liz Hoffman", "user_profile_image"=>"http://a0.twimg.com/profile_images/1923084945/Liz_H_normal.JPG"}
• {"id"=>"370540594973532161", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data, new paper by @TahaYasseri et al. http://t.co/Asfo34RY8Z", "created_at"=>"2013-08-22T13:38:56Z", "user"=>"danicar", "user_name"=>"Danica Radovanović", "user_profile_image"=>"http://a0.twimg.com/profile_images/2346665234/jy1pimbg0ok7qrv981gq_normal.jpeg"}
• {"id"=>"370596849855377408", "text"=>"Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2013-08-22T17:22:29Z", "user"=>"ThatNeilMartin", "user_name"=>"Dr Neil Martin", "user_profile_image"=>"http://a0.twimg.com/profile_images/3476595279/9f884431535b213cb1de9ffdee8ddd6c_normal.png"}
• {"id"=>"370736853848043520", "text"=>"PLOS ONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/8dhyNlyjhZ", "created_at"=>"2013-08-23T02:38:48Z", "user"=>"pdorje", "user_name"=>"Eduardo Pinheiro", "user_profile_image"=>"http://a0.twimg.com/profile_images/51983239/DSC00505_normal.jpg"}
• {"id"=>"370791328210493440", "text"=>"Wikipedia activity predicts film box office performance a month in advance: http://t.co/0m9HMcUH9Z 77% accuracy, works best on blockbusters.", "created_at"=>"2013-08-23T06:15:16Z", "user"=>"JWShield", "user_name"=>"James Shield", "user_profile_image"=>"http://a0.twimg.com/profile_images/3650331371/2cf3a3a5325965f0450a0f16a39a1308_normal.png"}
• {"id"=>"370820490765430784", "text"=>"Plos One on #bigdata: how many tools can be as versatile as a think framework? http://t.co/YTQCqexLh1", "created_at"=>"2013-08-23T08:11:09Z", "user"=>"enriketto", "user_name"=>"Enrico Dallò", "user_profile_image"=>"http://a0.twimg.com/profile_images/73071203/enri_small_normal.jpg"}
• {"id"=>"370822952616333312", "text"=>"#PLOSONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/l5j6KeZVuc", "created_at"=>"2013-08-23T08:20:56Z", "user"=>"monzoneta", "user_name"=>"Esther Monzó", "user_profile_image"=>"http://a0.twimg.com/profile_images/3762037512/e2baedd2d31e11cd3f5c0642875611b4_normal.jpeg"}
• {"id"=>"370863665173757952", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/HchUY6cZEA", "created_at"=>"2013-08-23T11:02:42Z", "user"=>"SamCreavin", "user_name"=>"Sam Creavin", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000114789215/bc4fc86c44efba1bb3b61f9f63be8785_normal.jpeg"}
• {"id"=>"370886469763997696", "text"=>"RT @SamCreavin: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/HchUY6cZEA", "created_at"=>"2013-08-23T12:33:19Z", "user"=>"Anas_ET", "user_name"=>"Anas ET", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000302657505/7565ad2a228a60bbc9fdae74775c22f1_normal.jpeg"}
• {"id"=>"370888959112806400", "text"=>"Using data to predict box office success for film releases l http://t.co/9tm8vIYFYe", "created_at"=>"2013-08-23T12:43:13Z", "user"=>"Media_Synergy", "user_name"=>"MEDIA SYNERGY", "user_profile_image"=>"http://a0.twimg.com/profile_images/2565516825/wdpyjuf3y90tf3thmgg5_normal.jpeg"}
• {"id"=>"370942732271116288", "text"=>"RT @Media_Synergy: Using data to predict box office success for film releases l http://t.co/9tm8vIYFYe", "created_at"=>"2013-08-23T16:16:53Z", "user"=>"hgaldinoshea", "user_name"=>"Helene Galdin-O'Shea", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000330559768/b815a43eed3f463b945d5a069ffa39fe_normal.jpeg"}
• {"id"=>"370942750516342784", "text"=>"RT @Media_Synergy: Using data to predict box office success for film releases l http://t.co/9tm8vIYFYe", "created_at"=>"2013-08-23T16:16:58Z", "user"=>"parkhighmedia", "user_name"=>"Park High Media", "user_profile_image"=>"http://a0.twimg.com/profile_images/1236644509/logo_normal.jpg"}
• {"id"=>"370943578622537728", "text"=>"What applications does \"big data\" have other than NGS? How about predicting blockbusters? Check it out: http://t.co/Oh0Mkk0NKb", "created_at"=>"2013-08-23T16:20:15Z", "user"=>"NGSRamiZahr", "user_name"=>"Rami Zahr", "user_profile_image"=>"http://a0.twimg.com/sticky/default_profile_images/default_profile_0_normal.png"}
• {"id"=>"370986389753839616", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity #BigData http://t.co/LR4Lar6zRP via @plosone", "created_at"=>"2013-08-23T19:10:22Z", "user"=>"mrxanalytics", "user_name"=>"Research & Analytics", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000049831236/5ff3a8f2e906ba6a64079474785740b6_normal.png"}
• {"id"=>"370991275677204481", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data article in @PLOS http://t.co/Y2dXgZo6QN", "created_at"=>"2013-08-23T19:29:47Z", "user"=>"CommonCrawl", "user_name"=>"CommonCrawl", "user_profile_image"=>"http://a0.twimg.com/profile_images/1616236973/square-name-white_normal.png"}
• {"id"=>"370991479604273152", "text"=>"RT @CommonCrawl: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data article in @PLOS http://t.co/Y2dXgZo6QN", "created_at"=>"2013-08-23T19:30:36Z", "user"=>"boudicca", "user_name"=>"Lisa Green", "user_profile_image"=>"http://a0.twimg.com/profile_images/1534144474/Lisa_Green_headshot_2_normal.jpg"}
• {"id"=>"371039742898757632", "text"=>"#PLOSONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/4zfO8pXj0G", "created_at"=>"2013-08-23T22:42:22Z", "user"=>"ysirod", "user_name"=>"Yair Sifnugel R.", "user_profile_image"=>"http://a0.twimg.com/profile_images/1498277350/img457891a_normal.jpg"}
• {"id"=>"371057572175822848", "text"=>"Off-topic but interesting: Box-office flops accurately predictable by monitoring the movie's Wikipedia views & edits http://t.co/Fv4Nfl49SJ", "created_at"=>"2013-08-23T23:53:13Z", "user"=>"randomdijit", "user_name"=>"Jake Turk", "user_profile_image"=>"http://a0.twimg.com/profile_images/1208897759/t_normal.jpg"}
• {"id"=>"371066126341386240", "text"=>"Very cool. Early Wikipedia “collaborative rigor” predicts movie box office success: http://t.co/XE9TCDDNUh\n#timeseries #analytics #bigdata", "created_at"=>"2013-08-24T00:27:13Z", "user"=>"kennwhite", "user_name"=>"Kenn White", "user_profile_image"=>"http://a0.twimg.com/profile_images/2409299713/m4lsp3hhev776f6zogc9_normal.jpeg"}
• {"id"=>"371067125823451138", "text"=>"RT @kennwhite: Very cool. Early Wikipedia “collaborative rigor” predicts movie box office success: http://t.co/XE9TCDDNUh\n#timeseries #anal…", "created_at"=>"2013-08-24T00:31:11Z", "user"=>"PageViral", "user_name"=>"PageViral Inc", "user_profile_image"=>"http://a0.twimg.com/profile_images/3392735290/0d51aa1b0f3dc78d5376bab09827e8ce_normal.png"}
• {"id"=>"371151059894681600", "text"=>"RT @CommonCrawl: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data article in @PLOS http://t.co/Y2dXgZo6QN", "created_at"=>"2013-08-24T06:04:43Z", "user"=>"srockets", "user_name"=>"srockets", "user_profile_image"=>"http://a0.twimg.com/profile_images/3505477242/50b93930cf2123d586fd3849015d4b14_normal.png"}
• {"id"=>"371229697960468480", "text"=>"Participation & prediction: how #Wikipedia helps to understand if a movie will be a blockbuster http://t.co/okTK6rUkO5", "created_at"=>"2013-08-24T11:17:11Z", "user"=>"henrimonceau", "user_name"=>"Henri Monceau", "user_profile_image"=>"http://a0.twimg.com/profile_images/1650137096/Instantan__vid_o-96_normal.jpeg"}
• {"id"=>"371268176408899585", "text"=>"Spooky prediction of box office success based on Wikipedia sabremetrics http://t.co/3FBFfQdVME", "created_at"=>"2013-08-24T13:50:05Z", "user"=>"earlstoner", "user_name"=>"Earl S. Stoner, Esq.", "user_profile_image"=>"http://a0.twimg.com/profile_images/1181953640/ScanImage304_normal.jpg"}
• {"id"=>"371273202250420225", "text"=>"Collective prediction: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/SVLHIsS2yg", "created_at"=>"2013-08-24T14:10:04Z", "user"=>"GTheraulaz", "user_name"=>"Guy Theraulaz", "user_profile_image"=>"http://a0.twimg.com/profile_images/2482427527/image_normal.jpg"}
• {"id"=>"371342201239789568", "text"=>"#Wikipedia peut dire si un #film sera un succès ou un flop. #calcul #mathematique #database #chercheur #boxoffice http://t.co/P9LVK2gkgh", "created_at"=>"2013-08-24T18:44:14Z", "user"=>"RochJeremy", "user_name"=>"Jeremy Roch", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000232349591/a83330002390ed8ec9d549b07a134f36_normal.jpeg"}
• {"id"=>"371371506900545536", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/06hjClQE8j via http://t.co/OMg8TlrcbV", "created_at"=>"2013-08-24T20:40:41Z", "user"=>"johnwalling", "user_name"=>"John Walling", "user_profile_image"=>"http://a0.twimg.com/profile_images/1211545984/booth-dog-head-yellow_normal.png"}
• {"id"=>"371371580091154432", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/06hjClQE8j \nvia http://t.co/OMg8TlrcbV", "created_at"=>"2013-08-24T20:40:59Z", "user"=>"johnwalling", "user_name"=>"John Walling", "user_profile_image"=>"http://a0.twimg.com/profile_images/1211545984/booth-dog-head-yellow_normal.png"}
• {"id"=>"371543985115762688", "text"=>"'Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data' PLoS One http://t.co/XfvDGe4kKQ", "created_at"=>"2013-08-25T08:06:03Z", "user"=>"eltonjohn", "user_name"=>"Samantha Clark", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000260626643/cb759654bafa5b62ee6cb15b5067f66b_normal.jpeg"}
• {"id"=>"371708637749604352", "text"=>"@brianstorms Unrelate, you saw this? http://t.co/r1HSofVeW8", "created_at"=>"2013-08-25T19:00:19Z", "user"=>"pkedrosky", "user_name"=>"Paul Kedrosky", "user_profile_image"=>"http://a0.twimg.com/profile_images/3293726938/94d9c55d04adce1174aefa25eb0d6a02_normal.jpeg"}
• {"id"=>"371725688656523264", "text"=>"Cute http://t.co/SM3LHxrjr7", "created_at"=>"2013-08-25T20:08:05Z", "user"=>"xinti900", "user_name"=>"Shang", "user_profile_image"=>"http://a0.twimg.com/profile_images/3056461734/03cb70dfb953200a4742f100b6b29ef8_normal.jpeg"}
• {"id"=>"371739279736975361", "text"=>"Using Wikipedia data to predict the success of a movie: PLOS ONE http://t.co/2Z0WIx6Y9b", "created_at"=>"2013-08-25T21:02:05Z", "user"=>"behaviorgames", "user_name"=>"Neil Schmitzer-Torbe", "user_profile_image"=>"http://a0.twimg.com/profile_images/3572781388/7817b6cda52f570ac799a10c599ce845_normal.jpeg"}
• {"id"=>"372261985934508032", "text"=>"Wikipedia kan het kassucces van een film voorspellen http://t.co/BUsNA0GW2l", "created_at"=>"2013-08-27T07:39:08Z", "user"=>"VSNAmsterdam", "user_name"=>"Van Santen Netwerk", "user_profile_image"=>"http://a0.twimg.com/profile_images/1300638263/VSN_ster_normal.JPG"}
• {"id"=>"372405592289050624", "text"=>"\"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data\". \nSigh. \nhttp://t.co/j0JY00pdGN", "created_at"=>"2013-08-27T17:09:46Z", "user"=>"LauraDeming", "user_name"=>"Laura Deming", "user_profile_image"=>"http://a0.twimg.com/profile_images/1846498068/Professional_Photo_2_-_Small_normal.jpg"}
• {"id"=>"372572888215191553", "text"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/zIcX6vAZSB", "created_at"=>"2013-08-28T04:14:33Z", "user"=>"sebaspro92", "user_name"=>"Sebastian Carrasco", "user_profile_image"=>"http://a0.twimg.com/profile_images/3406879564/165a0b02ba60337ddd8b8ec4a7f63eb6_normal.jpeg"}
• {"id"=>"372667991583756290", "text"=>"Prédire grâce à #Wikipedia le succès d’un film ou pas ... #cinema http://t.co/Xj7rPRZk4L", "created_at"=>"2013-08-28T10:32:27Z", "user"=>"troover", "user_name"=>"F. JEANNE-BEYLOT", "user_profile_image"=>"http://a0.twimg.com/profile_images/1930216293/fjb_old_pt_normal.jpg"}
• {"id"=>"372743812629954560", "text"=>"Aug 23 2013 #Econometrics PLOS ONE 8.8 #journals#TimeSeries #BigData #WikipediaMestiánYasseriKertész2013 #OA http://t.co/BPKAcsBLFC", "created_at"=>"2013-08-28T15:33:44Z", "user"=>"econlinks", "user_name"=>"Marius Ooms", "user_profile_image"=>"http://a0.twimg.com/profile_images/1850799572/bee_normal.gif"}
• {"id"=>"373625573480079360", "text"=>"#BigData goes to the #Movies: Predicting Box Office Success using pre-release Wikipedia activity http://t.co/BYVAIMbUsg @PLOSONE via @SSRN", "created_at"=>"2013-08-31T01:57:33Z", "user"=>"davidslocum", "user_name"=>"David Slocum", "user_profile_image"=>"http://a0.twimg.com/profile_images/265327651/s742142601_1252750_9617_normal.jpg"}
• {"id"=>"373931279471108097", "text"=>"RT @davidslocum: #BigData goes to the #Movies: Predicting Box Office Success using pre-release Wikipedia activity http://t.co/BYVAIMbUsg @P…", "created_at"=>"2013-08-31T22:12:19Z", "user"=>"SSRN", "user_name"=>"SSRN", "user_profile_image"=>"http://a0.twimg.com/profile_images/126797573/SSRNreflected_SMALL_normal.jpg"}
• {"id"=>"374062461999407104", "text"=>"RT @davidslocum: #BigData goes to the #Movies: Predicting Box Office Success using pre-release Wikipedia activity http://t.co/BYVAIMbUsg @P…", "created_at"=>"2013-09-01T06:53:35Z", "user"=>"RiccaboniM", "user_name"=>"massimo riccaboni", "user_profile_image"=>"http://a0.twimg.com/profile_images/2924194483/790b4b3b617ef5167e6bab21596893f5_normal.jpeg"}
• {"id"=>"374207583953117186", "text"=>"RT @davidslocum: #BigData goes to the #Movies: Predicting Box Office Success using pre-release Wikipedia activity http://t.co/BYVAIMbUsg @P…", "created_at"=>"2013-09-01T16:30:15Z", "user"=>"ghirardinicola", "user_name"=>"ghirardi nicola", "user_profile_image"=>"http://a0.twimg.com/profile_images/1370760921/GreenIdeas_normal.jpg"}
• {"id"=>"374232947710103553", "text"=>"Comment prévoir le succès ou l'échec d'un nouveau film grâce à Wikipedia http://t.co/8XVVpXaDHn", "created_at"=>"2013-09-01T18:11:02Z", "user"=>"Hgibier", "user_name"=>"Henri Gibier", "user_profile_image"=>"http://a0.twimg.com/profile_images/1339665345/94_2010_normal.png"}
• {"id"=>"374552792783810560", "text"=>"#PLOSONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/lEDYWMzc4U", "created_at"=>"2013-09-02T15:21:59Z", "user"=>"mehdikhaneboubi", "user_name"=>"khaneboubi", "user_profile_image"=>"http://a0.twimg.com/profile_images/2268901915/ev2otfg80507f2zvqfdh_normal.gif"}
• {"id"=>"374736296704360449", "text"=>"RT @Hgibier: Comment prévoir le succès ou l'échec d'un nouveau film grâce à Wikipedia http://t.co/8XVVpXaDHn", "created_at"=>"2013-09-03T03:31:10Z", "user"=>"LauChiapponi", "user_name"=>"Laurence CHIAPPONI", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000289295776/2e35d070e64f9475318e221c7e9d0ce6_normal.jpeg"}
• {"id"=>"374736397581959168", "text"=>"RT @Hgibier: Comment prévoir le succès ou l'échec d'un nouveau film grâce à Wikipedia http://t.co/8XVVpXaDHn", "created_at"=>"2013-09-03T03:31:34Z", "user"=>"CitationsCinemx", "user_name"=>"Citations du Cinéma ", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000354021057/2e7e7beaf752d150efa977cfdaa90709_normal.jpeg"}
• {"id"=>"376995911056240640", "text"=>"PLOS ONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity (Big Data) http://t.co/el59XPc5TR - fascinating", "created_at"=>"2013-09-09T09:10:04Z", "user"=>"Indy_Neogy", "user_name"=>"Indy Neogy", "user_profile_image"=>"http://a0.twimg.com/profile_images/2902522604/0348728c788b3574ea14dab495794449_normal.png"}
• {"id"=>"377002394996842496", "text"=>"RT @Indy_Neogy: PLOS ONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity (Big Data) http://t.co/el59XPc5TR - fasc…", "created_at"=>"2013-09-09T09:35:50Z", "user"=>"kilnco", "user_name"=>"KILN Innovation", "user_profile_image"=>"http://a0.twimg.com/profile_images/1175235100/daboxfortwitterpic_normal.jpg"}
• {"id"=>"380993856243654658", "text"=>"Predicting #movieboxoffice success based on #wikipedia activity: Great paper by my @oiioxford colleague @TahaYasseri http://t.co/mnUs1rYzsT", "created_at"=>"2013-09-20T09:56:28Z", "user"=>"slavacm", "user_name"=>"Vyacheslav Polonski", "user_profile_image"=>"http://a0.twimg.com/profile_images/3678579875/e0cfa5c8fc4d664665ed4501e2e17357_normal.jpeg"}
• {"id"=>"387644348650635265", "text"=>"Using @Wikipedia data to predict box office success. #BigData http://t.co/l3FhRyXipn", "created_at"=>"2013-10-08T18:23:09Z", "user"=>"lumina_insights", "user_name"=>"Lumina Insights", "user_profile_image"=>"http://a0.twimg.com/profile_images/378800000530203674/96c3145fb4e90df87c2a32de7337ff7f_normal.jpeg"}
• {"id"=>"393351112071204864", "text"=>"Wow, Mathematiker aus Oxford berechnen den Erfolg eines Kinofilms im Voraus. Und das klappt!! http://t.co/Mfhm75tt9h #bigdata", "created_at"=>"2013-10-24T12:19:47Z", "user"=>"FilmTVundMedien", "user_name"=>"Film,- TV- u. Medien", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1794463299/FilmTVMedienLogo_normal.jpg"}
• {"id"=>"400753995062321152", "text"=>"Wikipedia의 데이타를 이용하여 영화매출액을 예측하는 논문입니다. 경진대회에 도움이 될것 같습니다. http://t.co/Cv7WVY9kq9", "created_at"=>"2013-11-13T22:36:12Z", "user"=>"koreauniv_stats", "user_name"=>"고려대학교 응용통계학과", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000736449503/42936d0d4ee981bf30a765c70ac004ae_normal.png"}
• {"id"=>"421410118538764289", "text"=>"Thank you @riyazifarook. The paper is available at http://t.co/u9z0A30qnF @BBCWorld", "created_at"=>"2014-01-09T22:36:16Z", "user"=>"TahaYasseri", "user_name"=>"Taha Yasseri", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2094692556/met_normal.jpg"}
• {"id"=>"421427048377495552", "text"=>"RT @TahaYasseri: Thank you @riyazifarook. The paper is available at http://t.co/u9z0A30qnF @BBCWorld", "created_at"=>"2014-01-09T23:43:32Z", "user"=>"denisparra", "user_name"=>"denisparra", "user_profile_image"=>"http://pbs.twimg.com/profile_images/3150064833/355871ecf6555b8de309174fd34415df_normal.jpeg"}
• {"id"=>"422356031554224128", "text"=>"RT @TahaYasseri: Thank you @riyazifarook. The paper is available at http://t.co/u9z0A30qnF @BBCWorld", "created_at"=>"2014-01-12T13:14:59Z", "user"=>"abellogin", "user_name"=>"Alejandro Bellogin", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2517843532/znl8xewn2j7jbm7386qd_normal.jpeg"}
• {"id"=>"444433818850967552", "text"=>"@fabiocurzi http://t.co/SmIKZrz0vv", "created_at"=>"2014-03-14T11:24:14Z", "user"=>"LuckBil", "user_name"=>"Billy Luca", "user_profile_image"=>"http://pbs.twimg.com/profile_images/411901475292340224/DbTVYKuL_normal.jpeg"}
• {"id"=>"466867623888953344", "text"=>"http://t.co/oY9JwrlgXC wikipedia activity can predict movies revenues, but works better with blockbusters than indie. I wonder about profits", "created_at"=>"2014-05-15T09:08:10Z", "user"=>"danielebarch", "user_name"=>"daniele", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2321837572/wlk48pliqegjbd6kq1lc_normal.png"}
• {"id"=>"575148530970402816", "text"=>"#PLOSONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data http://t.co/aDa2DOG7dC", "created_at"=>"2015-03-10T04:17:50Z", "user"=>"sprawesh", "user_name"=>"shankar Prawesh", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000709747069/b37c30634a020fb6094cba5da0aef1ba_normal.jpeg"}
• {"id"=>"609018032875147264", "text"=>"Which films will be summer blockbusters? Wikipedia predicts them. http://t.co/Na9dzCxMZJ", "created_at"=>"2015-06-11T15:23:08Z", "user"=>"stellayu", "user_name"=>"Stella Yu", "user_profile_image"=>"http://pbs.twimg.com/profile_images/3537911840/bae0125381af218d4aa69e3a8dace61d_normal.jpeg"}
• {"id"=>"778330163364835329", "text"=>"i will try this: https://t.co/DNsONmeN47", "created_at"=>"2016-09-20T20:29:06Z", "user"=>"TobiasWildman", "user_name"=>"Tobias Wildman Burns", "user_profile_image"=>"http://pbs.twimg.com/profile_images/773216952898596864/-3cPDsxV_normal.jpg"}
• {"id"=>"803212660896632832", "text"=>"RT @ThatNeilMartin: Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2016-11-28T12:23:15Z", "user"=>"TahaYasseri", "user_name"=>"Taha Yasseri", "user_profile_image"=>"http://pbs.twimg.com/profile_images/553330447413833729/mShUX9ZG_normal.jpeg"}
• {"id"=>"803212763636105216", "text"=>"RT @ThatNeilMartin: Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2016-11-28T12:23:40Z", "user"=>"AkinUnver", "user_name"=>"Akin Unver", "user_profile_image"=>"http://pbs.twimg.com/profile_images/791262402838945796/UXHyF0mF_normal.jpg"}
• {"id"=>"803213434183630848", "text"=>"RT @ThatNeilMartin: Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2016-11-28T12:26:20Z", "user"=>"FlemmingMa", "user_name"=>"Flemming Madsen", "user_profile_image"=>"http://pbs.twimg.com/profile_images/558656293284483072/X3vBfVxX_normal.jpeg"}
• {"id"=>"803213996593594368", "text"=>"RT @ThatNeilMartin: Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2016-11-28T12:28:34Z", "user"=>"anneohirsch", "user_name"=>"Anne Oeldorf-Hirsch", "user_profile_image"=>"http://pbs.twimg.com/profile_images/793990741370531840/ZKnmelg-_normal.jpg"}
• {"id"=>"803240010115792896", "text"=>"RT @ThatNeilMartin: Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2016-11-28T14:11:56Z", "user"=>"metebalci", "user_name"=>"Mete Balci", "user_profile_image"=>"http://pbs.twimg.com/profile_images/181205290/me_normal.jpg"}
• {"id"=>"803843776389283840", "text"=>"PLOS ONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data https://t.co/R1IGM33z06", "created_at"=>"2016-11-30T06:11:05Z", "user"=>"travisbickle31", "user_name"=>"Galata!", "user_profile_image"=>"http://pbs.twimg.com/profile_images/726202757607100416/5w4GxF6g_normal.jpg"}
• {"id"=>"803989101762342912", "text"=>"RT @ThatNeilMartin: Can Wikipedia predict a film's popularity before its release? http://t.co/XIgzrpY1Ar @TheMichaelMoran", "created_at"=>"2016-11-30T15:48:33Z", "user"=>"reiver", "user_name"=>"@reiver (Charles)", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1542967349/reiver-star_normal.png"}
• {"id"=>"887219696268972033", "text"=>"7.) Prediction of box office success is already possible, for instance via Wikipedia data (see @TahaYasseri’s work: https://t.co/9hm05NNCAN)", "created_at"=>"2017-07-18T07:57:13Z", "user"=>"_FelixSimon_", "user_name"=>"Felix Simon", "user_profile_image"=>"http://pbs.twimg.com/profile_images/824585704936202240/8dY6pfz9_normal.jpg"}
• {"id"=>"899852395492118528", "text"=>"PLOS ONE: Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data https://t.co/viyZXlD3Td", "created_at"=>"2017-08-22T04:35:04Z", "user"=>"pdorje", "user_name"=>"Eduardo Pinheiro", "user_profile_image"=>"http://pbs.twimg.com/profile_images/51983239/DSC00505_normal.jpg"}

Wikipedia | Further Information

• {"title"=>"Pageview", "url"=>"http://en.wikipedia.org/wiki/Pageview", "timestamp"=>"2019-02-20T00:59:02Z"}
• {"title"=>"Academic studies about Wikipedia", "url"=>"http://en.wikipedia.org/wiki/Academic_studies_about_Wikipedia", "timestamp"=>"2019-02-18T19:19:43Z"}
• {"title"=>"File:Operationalizing-conflict-bots-wikipedia-cscw-preprint.pdf", "url"=>"http://commons.wikimedia.org/wiki/File:Operationalizing-conflict-bots-wikipedia-cscw-preprint.pdf", "timestamp"=>"2017-09-18T00:26:28Z"}

Wordpress.com | Further Information

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• {"month"=>"4", "year"=>"2018", "pdf_views"=>"137", "xml_views"=>"3", "html_views"=>"310"}
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• {"month"=>"7", "year"=>"2018", "pdf_views"=>"75", "xml_views"=>"7", "html_views"=>"166"}
• {"month"=>"8", "year"=>"2018", "pdf_views"=>"210", "xml_views"=>"3", "html_views"=>"139"}
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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/1178406"], "description"=>"<p>A: Time of creation of the corresponding article in Wikipedia, shown in days of <i>movie time</i> ( is the release time), B: Release weekend box office revenue in the U. S., in USD C: <i>number of theaters</i> that screened the movie on the first weekend, D: Accumulated <i>number of views</i>, and E: <i>users</i>, F: <i>edits</i>, G: <i>rigor</i> for the Wikipedia page up to days after release.</p>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "variables", "movies"], "article_id"=>779326, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Histograms_of_different_variables_for_our_sample_of_movies_from_2010_/779326", "title"=>"Histograms of different variables for our sample of movies from 2010.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-21 02:15:59"}
• {"files"=>["https://ndownloader.figshare.com/files/1178408"], "description"=>"<p>The shorthands , , , , and denote the <i>number of views</i>, the <i>number of users</i>, the <i>rigor</i>, the <i>number of edits</i>, and the <i>number of theaters</i>, respectively. Time is measured in movie time. <i>Inset</i>: magnified detail of the main panel, showing the Pearson correlation around the day of release. Dashed horizontal line shows the correlation for <i>the number of theaters</i>.</p>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "pearson"], "article_id"=>779328, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temporal_evolution_of_the_Pearson_correlation_of_the_box_office_revenue_with_different_predictors_/779328", "title"=>"Temporal evolution of , the Pearson correlation of the box office revenue with different predictors.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-21 02:15:59"}
• {"files"=>["https://ndownloader.figshare.com/files/1178409"], "description"=>"<p>The shorthands , , , , and denote the <i>number of views</i>, the <i>number of users</i>, the <i>rigor</i>, the <i>number of edits</i>, and the <i>number of theaters</i>, respectively. The coefficient of determination was calculated using 10-fold cross-validation (see the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071226#s4\" target=\"_blank\">Methods</a> section). The dashed gray line shows the coefficient of determination for linear regression solely based on the <i>number of theaters</i>.</p>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "multivariate", "linear", "regression", "fed"], "article_id"=>779329, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Coefficient_of_determination_of_the_multivariate_linear_regression_model_fed_by_different_set_of_input_variables_/779329", "title"=>"Coefficient of determination of the multivariate linear regression model fed by different set of input variables.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-21 02:15:59"}
• {"files"=>["https://ndownloader.figshare.com/files/1178410"], "description"=>"<p>Same sample of 24 movies is considered as both training and test set. The coefficient of determination obtained with the Twitter-based method is 0.98 at the night of the release (day 0 in movie time).</p>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "twitter-based", "asur", "huberman"], "article_id"=>779330, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_results_with_the_Twitter_based_prediction_in_Asur_and_Huberman_work_27_/779330", "title"=>"Comparison of the results with the Twitter-based prediction in Asur and Huberman work [27].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-21 02:15:59"}
• {"files"=>["https://ndownloader.figshare.com/files/1178412"], "description"=>"<p>Green dots are representing the smaller sample of 24 movies common in Twitter and Wikipedia studies, and black dots are movies from the 2010 sample of 312 movies. Note that negative predicted revenues for some of the very unpopular movies could not be shown in the logarithmic scale.</p>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "wikipedia"], "article_id"=>779332, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_First_weekend_box_office_revenue_in_the_U_S_against_its_predicted_value_by_the_Wikipedia_model_at_days_/779332", "title"=>"First weekend box office revenue in the U. S. against its predicted value by the Wikipedia model at days.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-21 02:15:59"}
• {"files"=>["https://ndownloader.figshare.com/files/1178413"], "description"=>"<p>Each tick on the axis represents a modification of the page. Different tick styles refer to different users.</p>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "variables", "characterizing", "wikipedia", "editors"], "article_id"=>779333, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_different_variables_characterizing_the_activity_of_Wikipedia_editors_on_an_article_/779333", "title"=>"Illustration of different variables characterizing the activity of Wikipedia editors on an article.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-21 02:15:59"}
• {"files"=>["https://ndownloader.figshare.com/files/1178415", "https://ndownloader.figshare.com/files/1178416"], "description"=>"<div><p>Use of socially generated “big data” to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between “real time monitoring” and “early predicting” remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.</p></div>", "links"=>[], "tags"=>["Computer applications", "Web-based applications", "Applied mathematics", "Complex systems", "statistics", "Interdisciplinary physics", "Statistical mechanics", "communications", "Media studies", "Sociology", "Computational sociology", "culture", "Social research", "wikipedia"], "article_id"=>779335, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics", "Sociology"], "users"=>["Márton Mestyán", "Taha Yasseri", "János Kertész"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0071226.s001", "https://dx.doi.org/10.1371/journal.pone.0071226.s002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Early_Prediction_of_Movie_Box_Office_Success_Based_on_Wikipedia_Activity_Big_Data_/779335", "title"=>"Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-08-21 02:15:59"}

PMC Usage Stats | Further Information

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Relative Metric

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F1000Prime