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{"title"=>"Quantifying social influence in an online cultural market", "type"=>"journal", "authors"=>[{"first_name"=>"Coco", "last_name"=>"Krumme", "scopus_author_id"=>"35100448500"}, {"first_name"=>"Manuel", "last_name"=>"Cebrian", "scopus_author_id"=>"8724466500"}, {"first_name"=>"Galen", "last_name"=>"Pickard", "scopus_author_id"=>"23990920300"}, {"first_name"=>"Sandy", "last_name"=>"Pentland", "scopus_author_id"=>"7102755925"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84860748202", "doi"=>"10.1371/journal.pone.0033785", "pui"=>"364774461", "pmid"=>"22590493", "scopus"=>"2-s2.0-84860748202", "issn"=>"19326203"}, "id"=>"73bff5c3-966e-31ce-b69f-1d5be97192d1", "abstract"=>"We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process--the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role.", "link"=>"http://www.mendeley.com/research/quantifying-social-influence-online-cultural-market", "reader_count"=>54, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Librarian"=>1, "Student > Doctoral Student"=>5, "Researcher"=>9, "Student > Ph. D. Student"=>18, "Student > Postgraduate"=>2, "Student > Master"=>8, "Other"=>3, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Librarian"=>1, "Student > Doctoral Student"=>5, "Researcher"=>9, "Student > Ph. D. Student"=>18, "Student > Postgraduate"=>2, "Student > Master"=>8, "Other"=>3, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Engineering"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>1, "Agricultural and Biological Sciences"=>1, "Arts and Humanities"=>4, "Business, Management and Accounting"=>12, "Physics and Astronomy"=>1, "Psychology"=>9, "Social Sciences"=>11, "Computer Science"=>10, "Economics, Econometrics and Finance"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>11}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>9}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>10}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>12}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>4}}, "reader_count_by_country"=>{"Colombia"=>1, "Netherlands"=>1, "United States"=>1, "China"=>1, "Japan"=>1, "United Kingdom"=>2, "Australia"=>2, "Peru"=>1, "Switzerland"=>2, "Spain"=>2}, "group_count"=>3}

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• http://doi.org/10.1016/j.ejor.2017.10.056
• http://doi.org/10.1145/3359222
• http://doi.org/10.1177/0190272516645603
• http://doi.org/10.1038/s41598-018-34203-2
• http://doi.org/10.1016/j.physa.2014.06.039
• http://doi.org/10.1287/mnsc.2015.2354
• http://doi.org/10.1007/s10288-015-0302-y
• http://doi.org/10.1371/journal.pone.0114046
• http://doi.org/10.1007/s11277-020-07818-w
• http://doi.org/10.2139/ssrn.3054728
• http://doi.org/10.1086/702899
• http://doi.org/10.1371/journal.pone.0098914
• http://doi.org/10.1371/journal.pone.0121934
• http://doi.org/10.1371/journal.pone.0177385
• http://doi.org/10.1002/nav.21879
• http://doi.org/10.1140/epjds/s13688-017-0108-6
• http://doi.org/10.1016/j.physa.2014.03.042

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• {"id"=>"204573438017413121", "text"=>"Quantifying Social Influence in an Online Cultural Market http://t.co/ohLiIcsC @PLoSONE", "created_at"=>"2012-05-21T14:04:43Z", "user"=>"pablohaya", "user_name"=>"Pablo Haya", "user_profile_image"=>"http://a0.twimg.com/profile_images/529505106/Photo_27_normal.jpg"}
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• {"id"=>"208362258013749248", "text"=>"Quantifying Social Influence in an Online Cultural Market http://t.co/ozw3YAii data from 14,000 users interaction to download songs", "created_at"=>"2012-06-01T01:00:08Z", "user"=>"Buzzsonic", "user_name"=>"Adrian Fusiarski", "user_profile_image"=>"http://a0.twimg.com/profile_images/1752286498/AdeBuzz_normal.jpg"}
• {"id"=>"208363046798766080", "text"=>"'Quantifying Social Influence in an Online Cultural Market' PDF vers. MIT study via @plosone http://t.co/JnAX40bh", "created_at"=>"2012-06-01T01:03:16Z", "user"=>"Buzzsonic", "user_name"=>"Adrian Fusiarski", "user_profile_image"=>"http://a0.twimg.com/profile_images/1752286498/AdeBuzz_normal.jpg"}
• {"id"=>"208451162385555456", "text"=>"RT @Buzzsonic: Quantifying Social Influence in an Online Cultural Market http://t.co/ozw3YAii data from 14,000 users interaction to download songs", "created_at"=>"2012-06-01T06:53:24Z", "user"=>"QCharriaut", "user_name"=>"Quentin Charriaut", "user_profile_image"=>"http://a0.twimg.com/profile_images/1523450392/koala_normal.jpg"}
• {"id"=>"208572393977954304", "text"=>"Quantifying Social Influence in an Online Cultural Market http://t.co/epURuE2Y data from 14,000 users interaction to download songs", "created_at"=>"2012-06-01T14:55:08Z", "user"=>"theindiefeed", "user_name"=>"theindiefeed", "user_profile_image"=>"http://a0.twimg.com/profile_images/1446578631/IndieFeed-Twitter-Image-Sma_normal.jpg"}
• {"id"=>"209365583479832576", "text"=>"Quality may prevail despite social influence (better songs are downloaded more regardless of social signals) http://t.co/sHxEonsh", "created_at"=>"2012-06-03T19:26:59Z", "user"=>"PolNeuro", "user_name"=>"Darren Schreiber", "user_profile_image"=>"http://a0.twimg.com/profile_images/1476957487/MeSmall_normal.jpg"}
• {"id"=>"209693686332801025", "text"=>"Krumme et al. reexamine Salganik et al.'s Cultural Market http://t.co/tGGAz1Zv There is predictability if you measure samples -> dls not dls", "created_at"=>"2012-06-04T17:10:45Z", "user"=>"billrand", "user_name"=>"billrand", "user_profile_image"=>"http://a0.twimg.com/profile_images/1266492557/bill_normal.jpg"}
• {"id"=>"212075169525661698", "text"=>"[SOCIO][COMU] Quantifying Social Influence in an Online Cultural Market http://t.co/jfJFj5wl", "created_at"=>"2012-06-11T06:53:55Z", "user"=>"BSPO1348", "user_name"=>"BSPO - UCLouvain", "user_profile_image"=>"http://a0.twimg.com/profile_images/1214653612/DSCN0046-small_normal.JPG"}
• {"id"=>"885425358371258368", "text"=>"Quantifying Social Influence in an Online Cultural Market https://t.co/g1roJeJwrI", "created_at"=>"2017-07-13T09:07:10Z", "user"=>"JDeanThomas", "user_name"=>"Jason Thomas", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2224359523/image_normal.jpg"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/640552"], "description"=>"<p>Inequality is shown for Experiment 1, world 3. RMSE of simulated market’s unpredictability is = 0.0017, and average of inequality is = 0.093.</p>", "links"=>[], "tags"=>["unpredictability"], "article_id"=>311041, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0033785.g004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inequality_top_and_unpredictability_bottom_over_the_course_of_the_market_with_alpha_8202_8202_900_/311041", "title"=>"Inequality (top) and unpredictability (bottom) over the course of the market, with alpha = 900.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-05-09 00:17:21"}
• {"files"=>["https://ndownloader.figshare.com/files/640464"], "description"=>"<p>A listen first selects which song(s) he will listen to, and after listening, decides whether or not to download the song. The first decision is made based on the appeal of a song; the second based on its quality. If a listener listens to more than one song, this process is repeated.</p>", "links"=>[], "tags"=>["two-step"], "article_id"=>310963, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0033785.g003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Song_selection_as_a_two_step_process_/310963", "title"=>"Song selection as a two-step process.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-05-09 00:16:03"}
• {"files"=>["https://ndownloader.figshare.com/files/330881", "https://ndownloader.figshare.com/files/330919", "https://ndownloader.figshare.com/files/331041", "https://ndownloader.figshare.com/files/331237"], "description"=>"<div><p>We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process–the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role.</p> </div>", "links"=>[], "tags"=>["quantifying"], "article_id"=>125334, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0033785.s001", "https://dx.doi.org/10.1371/journal.pone.0033785.s002", "https://dx.doi.org/10.1371/journal.pone.0033785.s003", "https://dx.doi.org/10.1371/journal.pone.0033785.s004"], "stats"=>{"downloads"=>9, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Quantifying_Social_Influence_in_an_Online_Cultural_Market/125334", "title"=>"Quantifying Social Influence in an Online Cultural Market", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-05-09 01:28:54"}
• {"files"=>["https://ndownloader.figshare.com/files/640725"], "description"=>"<p>Inequality is shown for Experiment 2, world 5. RMSE of simulated market’s unpredictability is = 0.0012, and average of inequality is = 0.0516.</p>", "links"=>[], "tags"=>["unpredictability"], "article_id"=>311223, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0033785.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inequality_top_and_unpredictability_bottom_over_the_course_of_the_market_with_alpha_8202_8202_200_/311223", "title"=>"Inequality (top) and unpredictability (bottom) over the course of the market, with alpha = 200.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-05-09 00:20:23"}
• {"files"=>["https://ndownloader.figshare.com/files/640267"], "description"=>"<p>Values are shown for quality and appeal corresponding to the 48 songs in Experiment 2, independent condition. <i>R</i>² = 0.012.</p>", "links"=>[], "tags"=>["computer science", "science policy"], "article_id"=>310760, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0033785.g001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Quality_and_appeal_are_independent_/310760", "title"=>"Quality and appeal are independent.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-05-09 00:12:40"}
• {"files"=>["https://ndownloader.figshare.com/files/640879"], "description"=>"*<p>NS = non-social</p>**<p>averaged from sub-populations</p><p>The inequality (measured by Gini) is a mean of the results of 8 worlds. In the original experiments, the value for non-social unpredictability was determined by taking subpopulation of the independent condition. The simulated value for unpredictability is determined from 8 simulated non-social worlds.</p>", "links"=>[], "tags"=>["unpredictability", "inequality", "simulated"], "article_id"=>311370, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0033785.t001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Values_of_unpredictability_and_inequality_from_simulated_polya_and_original_SDW_markets_/311370", "title"=>"Values of unpredictability and inequality from simulated (polya) and original (SDW) markets.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-09 00:22:50"}
• {"files"=>["https://ndownloader.figshare.com/files/640367"], "description"=>"<p>The availability of a position n describes the likelihood that a song in that position will be sampled (where n = 1 is the top left corner in Experiment 1, and the topmost position in Experiment 2, and n = 48 is the bottom right corner in Experiment 1 and the bottom of the column in Experiment 2). Availability serves as a multiplier in calculating the total probability of a song being sampled, given its position-independent appeal, and its position at a given time in the market. In Experiment 1 (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033785#pone-0033785-g002\" target=\"_blank\">Figure 2a</a>), songs on the left side of the grid are more likely to be sampled, all else equal, than songs on the right. In Experiment 2 (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033785#pone-0033785-g002\" target=\"_blank\">Figure 2b</a>), songs at the top of the column, as well as the final song, are more likely to be sampled.</p>", "links"=>[], "tags"=>["experiments", "indexed"], "article_id"=>310861, "categories"=>["Information And Computing Sciences", "Science Policy"], "users"=>["Coco Krumme", "Manuel Cebrian", "Galen Pickard", "Sandy Pentland"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0033785.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Availability_in_the_independent_world_of_Experiments_1_A_top_and_2_B_bottom_indexed_to_1_/310861", "title"=>"Availability in the independent world of Experiments 1 (A, top) and 2 (B, bottom), indexed to 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-05-09 00:14:21"}

PMC Usage Stats | Further Information

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Relative Metric

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F1000Prime