The emotional arcs of stories are dominated by six basic shapes
Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using a ‘big data’ lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotio...
Saved in:
| Published in | EPJ data science Vol. 5; no. 1; pp. 31 - 12 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
04.11.2016
Springer Nature B.V SpringerOpen |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2193-1127 2193-1127 |
| DOI | 10.1140/epjds/s13688-016-0093-1 |
Cover
Loading…
| Abstract | Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using a ‘big data’ lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories and forming patterns that are meaningful to us. Here, by classifying the emotional arcs for a filtered subset of 1,327 stories from Project Gutenberg’s fiction collection, we find a set of six core emotional arcs which form the essential building blocks of complex emotional trajectories. We strengthen our findings by separately applying matrix decomposition, supervised learning, and unsupervised learning. For each of these six core emotional arcs, we examine the closest characteristic stories in publication today and find that particular emotional arcs enjoy greater success, as measured by downloads. |
|---|---|
| AbstractList | Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using a ‘big data’ lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories and forming patterns that are meaningful to us. Here, by classifying the emotional arcs for a filtered subset of 1,327 stories from Project Gutenberg’s fiction collection, we find a set of six core emotional arcs which form the essential building blocks of complex emotional trajectories. We strengthen our findings by separately applying matrix decomposition, supervised learning, and unsupervised learning. For each of these six core emotional arcs, we examine the closest characteristic stories in publication today and find that particular emotional arcs enjoy greater success, as measured by downloads. Abstract Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using a ‘big data’ lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories and forming patterns that are meaningful to us. Here, by classifying the emotional arcs for a filtered subset of 1,327 stories from Project Gutenberg’s fiction collection, we find a set of six core emotional arcs which form the essential building blocks of complex emotional trajectories. We strengthen our findings by separately applying matrix decomposition, supervised learning, and unsupervised learning. For each of these six core emotional arcs, we examine the closest characteristic stories in publication today and find that particular emotional arcs enjoy greater success, as measured by downloads. |
| ArticleNumber | 31 |
| Author | Reagan, Andrew J Mitchell, Lewis Kiley, Dilan Danforth, Christopher M Dodds, Peter Sheridan |
| Author_xml | – sequence: 1 givenname: Andrew J surname: Reagan fullname: Reagan, Andrew J email: andrew.reagan@uvm.edu organization: University of Vermont – sequence: 2 givenname: Lewis surname: Mitchell fullname: Mitchell, Lewis organization: University of Adelaide – sequence: 3 givenname: Dilan surname: Kiley fullname: Kiley, Dilan organization: University of Vermont – sequence: 4 givenname: Christopher M surname: Danforth fullname: Danforth, Christopher M organization: University of Vermont – sequence: 5 givenname: Peter Sheridan surname: Dodds fullname: Dodds, Peter Sheridan organization: University of Vermont |
| BookMark | eNqFkU1PJCEQhslGk_XrNyyJ51aKbhr6sNlsjLomJl70TKqhUCYzzSy0yfrvZWxNzF48UZB6XgqeQ7Y3pYkY-wHiDKAT57Rd-XJeoO2NaQT0jRBD28A3diBhV4DUe5_q7-yklJUQAlqp2r4_YL_un4jTJs0xTbjmmF3hKfAypxyp1D1xnzZxwpk8H194if_4iCU6Xp5wS-WY7QdcFzp5X4_Yw9Xl_cWf5vbu-ubi923jFKi5wa7zoIOGUSuvhDA9yFYOwQmN0JJA6FyrJQ0uGIkanVLBGa-QvOkGM7RH7GbJ9QlXdpvjBvOLTRjt20HKjxbzHN2aLPnBoXMiaFnZDlAN9ZZRBFJuHAXWrNMla5vT32cqs12l51yfXyyYXklj-kHUrp9Ll8uplEzBujjj7p_mjHFtQdidAvumwC4KbFVgdwosVF7_x39M_TVpFrJUYnqk_Gm-L9BXb8Cgrg |
| CitedBy_id | crossref_primary_10_1007_s11747_024_01057_2 crossref_primary_10_1073_pnas_2018652117 crossref_primary_10_1093_llc_fqy062 crossref_primary_10_1371_journal_pone_0248402 crossref_primary_10_3389_fpsyg_2024_1436918 crossref_primary_10_7238_artnodes_v0i28_385684 crossref_primary_10_1093_joc_jqz014 crossref_primary_10_1371_journal_pone_0231529 crossref_primary_10_3390_e24020278 crossref_primary_10_1093_jcr_ucy067 crossref_primary_10_2964_jsik_2020_030 crossref_primary_10_3390_app11041645 crossref_primary_10_3390_socsci7120264 crossref_primary_10_1007_s40614_018_0170_9 crossref_primary_10_1080_15213269_2023_2255845 crossref_primary_10_2139_ssrn_4098951 crossref_primary_10_1371_journal_pone_0256153 crossref_primary_10_1007_s11002_024_09740_8 crossref_primary_10_7748_nr_2024_e1944 crossref_primary_10_1002_arcp_1085 crossref_primary_10_1162_leon_a_02396 crossref_primary_10_1108_EJM_12_2020_0912 crossref_primary_10_1177_15291006231161337 crossref_primary_10_1371_journal_pone_0251704 crossref_primary_10_7202_1082341ar crossref_primary_10_1080_10350330_2022_2128740 crossref_primary_10_1057_s41599_024_03955_w crossref_primary_10_1558_imre_43229 crossref_primary_10_2139_ssrn_2702484 crossref_primary_10_3156_jsoft_32_6_935 crossref_primary_10_1007_s41109_020_00269_z crossref_primary_10_5325_style_58_3_0272 crossref_primary_10_22148_001c_84475 crossref_primary_10_3389_fpsyg_2022_1040755 crossref_primary_10_1139_facets_2016_0079 crossref_primary_10_1016_j_ipm_2019_03_006 crossref_primary_10_1038_s41598_023_50229_7 crossref_primary_10_1145_3531535 crossref_primary_10_1111_csp2_176 crossref_primary_10_1073_pnas_2211715119 crossref_primary_10_1140_epjds_s13688_021_00260_3 crossref_primary_10_1007_s00283_022_10187_w crossref_primary_10_1016_j_enpol_2021_112705 crossref_primary_10_3389_fpsyg_2024_1431764 crossref_primary_10_1109_TCSS_2019_2931721 crossref_primary_10_1016_j_jbusres_2023_114289 crossref_primary_10_1016_j_poetic_2023_101793 crossref_primary_10_1007_s11280_021_00892_5 crossref_primary_10_1075_ni_23001_lev crossref_primary_10_1016_j_jbusres_2022_07_021 crossref_primary_10_1080_01605682_2019_1705194 crossref_primary_10_1007_s40558_018_0122_y crossref_primary_10_1080_15213269_2021_2006718 crossref_primary_10_1080_15213269_2024_2406945 crossref_primary_10_1371_journal_pone_0223833 crossref_primary_10_1111_tops_12710 crossref_primary_10_12937_itel_1_1_Reg_p005 crossref_primary_10_1515_zgl_2022_2051 crossref_primary_10_15446_lthc_v25n2_108784 crossref_primary_10_1007_s13157_024_01840_5 crossref_primary_10_1016_j_procs_2024_10_175 crossref_primary_10_1088_1742_5468_abe947 crossref_primary_10_1615_CritRevEukaryotGeneExpr_2023048915 crossref_primary_10_1016_j_chaos_2023_113934 crossref_primary_10_1242_jeb_245780 crossref_primary_10_3390_e22010126 crossref_primary_10_1177_0961463X211032201 crossref_primary_10_1007_s11747_021_00794_y crossref_primary_10_1109_TPAMI_2024_3480702 crossref_primary_10_1093_llc_fqaf018 crossref_primary_10_1515_fns_2020_0016 crossref_primary_10_1073_pnas_2406735121 crossref_primary_10_2964_jsik_2021_038 crossref_primary_10_1615_CritRevEukaryotGeneExpr_2022041298 crossref_primary_10_22148_001c_87937 crossref_primary_10_1017_ehs_2020_21 crossref_primary_10_3390_su122410241 crossref_primary_10_1007_s10115_023_01907_5 crossref_primary_10_1093_comnet_cnx023 crossref_primary_10_1073_pnas_2011695118 crossref_primary_10_3389_fcomp_2024_1444549 crossref_primary_10_1140_epjds_s13688_023_00397_3 crossref_primary_10_1111_oli_12406 crossref_primary_10_1007_s10824_025_09532_6 crossref_primary_10_1287_mksc_2022_1351 crossref_primary_10_1126_sciadv_adl2013 crossref_primary_10_1080_1472586X_2025_2463516 crossref_primary_10_3389_fpsyg_2021_599063 crossref_primary_10_1057_s41599_024_03147_6 crossref_primary_10_3389_fnins_2023_1125983 crossref_primary_10_1080_25742442_2025_2463888 crossref_primary_10_1177_20552076241251715 crossref_primary_10_1515_fns_2020_0007 crossref_primary_10_3390_mti6070057 crossref_primary_10_1140_epjds_s13688_023_00400_x crossref_primary_10_1057_s41599_023_01680_4 crossref_primary_10_1016_j_procs_2024_09_386 crossref_primary_10_1126_sciadv_aba2196 crossref_primary_10_1007_s10618_023_00979_9 crossref_primary_10_1038_s41598_023_29178_8 crossref_primary_10_1515_opar_2018_0017 crossref_primary_10_1615_CritRevEukaryotGeneExpr_2024052382 crossref_primary_10_9728_dcs_2023_24_4_755 crossref_primary_10_17680_erciyesiletisim_483510 crossref_primary_10_1093_jcr_ucab010 crossref_primary_10_3390_ai1010002 crossref_primary_10_1080_15213269_2023_2210841 crossref_primary_10_1027_1864_1105_a000252 crossref_primary_10_1111_zygo_12481 crossref_primary_10_1145_3392046 crossref_primary_10_3389_fpsyg_2020_574746 crossref_primary_10_1371_journal_pone_0274480 crossref_primary_10_1145_3359190 crossref_primary_10_1177_0022242919873106 crossref_primary_10_2139_ssrn_4190806 crossref_primary_10_1093_llc_fqad046 crossref_primary_10_1108_AAAJ_11_2016_2796 crossref_primary_10_1007_s13278_021_00854_9 crossref_primary_10_1016_j_pec_2021_07_043 crossref_primary_10_1016_j_erss_2017_05_030 crossref_primary_10_1080_15213269_2022_2103711 crossref_primary_10_1007_s11634_023_00567_1 crossref_primary_10_2139_ssrn_3198315 crossref_primary_10_2139_ssrn_3170954 crossref_primary_10_1177_07439156241300997 crossref_primary_10_1080_25741136_2022_2155371 crossref_primary_10_1016_j_ijgfs_2024_100943 crossref_primary_10_1080_02699931_2022_2031906 crossref_primary_10_3758_s13428_021_01697_0 crossref_primary_10_1007_s00146_025_02219_8 crossref_primary_10_2139_ssrn_3923683 crossref_primary_10_1038_s41562_024_01938_0 crossref_primary_10_1155_2022_8160695 |
| Cites_doi | 10.1080/01621459.1963.10500845 10.1142/S0219525916500053 10.1098/rsos.150645 10.1016/0377-0427(87)90125-7 10.1007/978-1-4614-3223-4_3 10.1037/1089-2680.2.2.175 10.1140/epjds/s13688-016-0085-1 10.1109/5.58325 10.1073/pnas.1411678112 10.7560/783911 10.1371/journal.pone.0026752 10.1109/ASONAM.2016.7752379 |
| ContentType | Journal Article |
| Copyright | Reagan et al. 2016 Reagan et al. 2016. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: Reagan et al. 2016 – notice: Reagan et al. 2016. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | C6C AAYXX CITATION 3V. 7X2 8FE 8FG 8FH 8FK ABJCF ABUWG AEUYN AFKRA ARAPS ATCPS AZQEC BBNVY BENPR BGLVJ BHPHI BKSAR CCPQU D1I DWQXO GNUQQ HCIFZ JQ2 K7- KB. L6V LK8 M0K M7P M7S P5Z P62 PATMY PCBAR PDBOC PHGZM PHGZT PIMPY PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY DOA |
| DOI | 10.1140/epjds/s13688-016-0093-1 |
| DatabaseName | SpringerOpen Free (Free internet resource, activated by CARLI) CrossRef ProQuest Central (Corporate) Agricultural Science Collection ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland Advanced Technologies & Aerospace Collection Agricultural & Environmental Science Collection ProQuest Central Essentials - QC Biological Science Collection ProQuest Central Technology Collection Natural Science Collection Earth, Atmospheric & Aquatic Science Collection ProQuest One ProQuest Materials Science Collection ProQuest Central Korea ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database Materials Science Database ProQuest Engineering Collection Biological Sciences Agriculture Science Database Biological Science Database Engineering Database ProQuest advanced technologies & aerospace journals ProQuest Advanced Technologies & Aerospace Collection Environmental Science Database Earth, Atmospheric & Aquatic Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering collection Environmental Science Collection DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef Agricultural Science Database Publicly Available Content Database Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Materials Science Collection ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Natural Science Collection ProQuest Central China Earth, Atmospheric & Aquatic Science Collection ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability ProQuest Engineering Collection Natural Science Collection ProQuest Central Korea Agricultural & Environmental Science Collection Biological Science Collection Materials Science Database ProQuest Central (New) Engineering Collection ProQuest Materials Science Collection Advanced Technologies & Aerospace Collection Engineering Database ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Earth, Atmospheric & Aquatic Science Database Agricultural Science Collection ProQuest Technology Collection Biological Science Database ProQuest SciTech Collection Environmental Science Collection Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition Materials Science & Engineering Collection Environmental Science Database ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) |
| DatabaseTitleList | Agricultural Science Database |
| Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 3 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) Computer Science |
| EISSN | 2193-1127 |
| EndPage | 12 |
| ExternalDocumentID | oai_doaj_org_article_ed9cacc0f7284941a5907ab0fe5cbb0a 4312436111 10_1140_epjds_s13688_016_0093_1 |
| GrantInformation_xml | – fundername: National Science Foundation grantid: 1447634 funderid: http://dx.doi.org/10.13039/100000001 |
| GroupedDBID | -A0 0R~ 5VS 7X2 7XC 8CJ 8FE 8FG 8FH AAFWJ AAJSJ AAKKN ABEEZ ABFTD ABJCF ACACY ACGFS ACULB ADBBV ADINQ ADMLS AEUYN AFGXO AFKRA AHBYD AHSBF AHYZX ALMA_UNASSIGNED_HOLDINGS AMKLP ARAPS ARCSS ATCPS BBNVY BCNDV BENPR BGLVJ BHPHI BKSAR C24 C6C CCPQU D1I D1J D1K EBLON EBS EJD GROUPED_DOAJ HCIFZ IPNFZ K6- K6V K7- KB. KQ8 L6V LK5 LK8 M0K M7P M7R M7S M~E OK1 P62 PATMY PCBAR PDBOC PIMPY PROAC PTHSS PYCSY RID RIG RSV SCO SOJ TUS 2VQ AASML AAYXX AFPKN CITATION HZ~ IAO ISR ITC O9- PHGZM PHGZT 3V. 8FK ABUWG AZQEC DWQXO GNUQQ JQ2 PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PUEGO |
| ID | FETCH-LOGICAL-c515t-a44d17f71b75d5008612329fc07a13e0a14c372e9cf82a7ac55fc8d5aed849893 |
| IEDL.DBID | C24 |
| ISSN | 2193-1127 |
| IngestDate | Wed Aug 27 01:19:36 EDT 2025 Fri Jul 25 11:11:00 EDT 2025 Tue Jul 01 02:11:22 EDT 2025 Thu Apr 24 22:53:26 EDT 2025 Fri Feb 21 02:34:40 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | society language stories narratology sentiment mining |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c515t-a44d17f71b75d5008612329fc07a13e0a14c372e9cf82a7ac55fc8d5aed849893 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| OpenAccessLink | https://link.springer.com/10.1140/epjds/s13688-016-0093-1 |
| PQID | 1865288690 |
| PQPubID | 2034770 |
| PageCount | 12 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_ed9cacc0f7284941a5907ab0fe5cbb0a proquest_journals_1865288690 crossref_citationtrail_10_1140_epjds_s13688_016_0093_1 crossref_primary_10_1140_epjds_s13688_016_0093_1 springer_journals_10_1140_epjds_s13688_016_0093_1 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2016-11-04 |
| PublicationDateYYYYMMDD | 2016-11-04 |
| PublicationDate_xml | – month: 11 year: 2016 text: 2016-11-04 day: 04 |
| PublicationDecade | 2010 |
| PublicationPlace | Berlin/Heidelberg |
| PublicationPlace_xml | – name: Berlin/Heidelberg – name: Heidelberg |
| PublicationTitle | EPJ data science |
| PublicationTitleAbbrev | EPJ Data Sci |
| PublicationYear | 2016 |
| Publisher | Springer Berlin Heidelberg Springer Nature B.V SpringerOpen |
| Publisher_xml | – name: Springer Berlin Heidelberg – name: Springer Nature B.V – name: SpringerOpen |
| References | Riedl MO, Harrison B (2015) Using stories to teach human values to artificial agents Jockers M (2014) A novel method for detecting plot. http://www.matthewjockers.net/2014/06/05/a-novel-method-for-detecting-plot RousseeuwPJSilhouettes: a graphical aid to the interpretation and validation of cluster analysisJ Comput Appl Math198720536510.1016/0377-0427(87)90125-70636.62059 VonnegutKPalm sunday1981New YorkRosettaBooks LLC Tenenbaum DJ, Barrett K, Medaris SV, Devitt T (2015) In 10 languages, happy words beat sad ones. http://whyfiles.org/2015/in-10-languages-happy-words-beat-sad-ones MorettiFDistant reading2013New YorkVerso GleickJThe information: a history, a theory, a flood2011New YorkPantheon DundesAThe motif-index and the tale type index: a critiqueJ Folklore Res199734195202 Munroe R (2009) Movie narrative charts. http://xkcd.com/657 UtherH-JThe types of international folktales. A classification and bibliography. Based on the system of Antti Aarne and Stith Thompson. Part I. Animal tales, tales of magic, religious tales, and realistic tales, with an introduction2011HelsinkiFinnish Academy of Science and Letters RibeiroFNAraújoMGonçalvesPGonçalvesMABenevenutoFSentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methodsEPJ Data Sci20165110.1140/epjds/s13688-016-0085-1 NenkovaAMcKeownKA survey of text summarization techniquesMining text data2012BerlinSpringer437610.1007/978-1-4614-3223-4_3 Vonnegut K (1995) Shapes of stories. https://www.youtube.com/watch?v=oP3c1h8v2ZQ LiBLee-UrbanSJohnstonGRiedlMStory generation with crowdsourced plot graphsProceedings of the twenty-seventh AAAI conference on artificial intelligence2013 Winston PH (2011) The strong story hypothesis and the directed perception hypothesis GottschallJThe storytelling animal: how stories make us human2013New YorkMariner Books Dodds PS (2013) Homo narrativus and the trouble with fame. Nautilus magazine. http://nautil.us/issue/5/fame/homo-narrativus-and-the-trouble-with-fame PratchettTStewartICohenJThe science of Discworld II: the globe2003LondonEbury Press CampbellJThe hero with a thousand faces20083NovatoNew World Library KirschenbaumMGThe remaking of reading: data mining and the digital humanitiesThe national science foundation symposium on next generation of data mining and cyber-enabled discovery for innovation2007 Bost X, Labatut V, Linarès G (2016) Narrative smoothing: dynamic conversational network for the analysis of TV series plots. arXiv:1602.07811 Various (2010) Project Gutenberg. http://gutenberg.org MinSParkJNarrative as a complex network: a study of Victor Hugo’s Les MisérablesProceedings of HCI Korea2016 DolbySKLiterary folkloristics and the personal narrative2008BloomingtonTrickster Press NickersonRSConfirmation bias: a ubiquitous phenomenon in many guisesRev Gen Psychol1998217522010.1037/1089-2680.2.2.175 da SilvaSGTehraniJJComparative phylogenetic analyses uncover the ancient roots of Indo-European folktalesR Soc Open Sci20163110.1098/rsos.150645http://rsos.royalsocietypublishing.org/content/3/1/150645.full.pdf ProppVMorphology of the folktale (1928)1968AustinUniversity of Texas Press BookerCThe seven basic plots: why we tell stories2006New YorkBloomsbury Academic DoddsPSHarrisKDKloumannIMBlissCADanforthCMTemporal patterns of happiness and information in a global social network: hedonometrics and TwitterPLoS ONE201161210.1371/journal.pone.0026752 DoddsPSClarkEMDesuSFrankMRReaganAJWilliamsJRMitchellLHarrisKDKloumannIMBagrowJPMegerdoomianKMcMahonMTTivnanBFDanforthCMHuman language reveals a universal positivity biasProc Natl Acad Sci USA201511282389239410.1073/pnas.1411678112 MacDonaldMRStorytellers sourcebook: a subject, title, and motif index to folklore collections for children1982Farmington HillsGale Group Reagan A, Tivnan B, Williams JR, Danforth CM, Dodds PS (2015) Benchmarking sentiment analysis methods for large-scale texts: a case for using continuum-scored words and word shift graphs. arXiv:1512.00531 KohonenTThe self-organizing mapProc IEEE19907891464148010.1109/5.58325 BexFJBench-CaponTJPersuasive stories for multi-agent argumentationAAAI fall symposium: computational models of narrative20104 Cave S (2013) The 4 stories we tell ourselves about death. http://www.ted.com/talks/stephen_cave_the_4_stories_we_tell_ourselves_about_death Prado SD, Dahmen SR, Bazzan ALC, Carron PM, Kenna R (2016) Temporal network analysis of literary texts. arXiv:1602.07275 WardJHJrHierarchical grouping to optimize an objective functionJ Am Stat Assoc19635830123624414818810.1080/01621459.1963.10500845 V Propp (93_CR8) 1968 K Vonnegut (93_CR18) 1981 FJ Bex (93_CR31) 2010 A Dundes (93_CR13) 1997; 34 T Kohonen (93_CR27) 1990; 78 MR MacDonald (93_CR9) 1982 B Li (93_CR30) 2013 93_CR23 H-J Uther (93_CR15) 2011 93_CR25 MG Kirschenbaum (93_CR16) 2007 93_CR20 PJ Rousseeuw (93_CR29) 1987; 20 RS Nickerson (93_CR6) 1998; 2 JH Ward Jr (93_CR26) 1963; 58 J Gleick (93_CR7) 2011 S Min (93_CR11) 2016 SK Dolby (93_CR14) 2008 PS Dodds (93_CR28) 2015; 112 F Moretti (93_CR17) 2013 J Gottschall (93_CR3) 2013 C Booker (93_CR24) 2006 93_CR33 93_CR12 93_CR34 T Pratchett (93_CR1) 2003 93_CR36 J Campbell (93_CR2) 2008 PS Dodds (93_CR22) 2011; 6 93_CR32 93_CR19 FN Ribeiro (93_CR21) 2016; 5 93_CR37 93_CR5 SG da Silva (93_CR10) 2016; 3 93_CR4 A Nenkova (93_CR35) 2012 |
| References_xml | – reference: Munroe R (2009) Movie narrative charts. http://xkcd.com/657/ – reference: MorettiFDistant reading2013New YorkVerso – reference: Vonnegut K (1995) Shapes of stories. https://www.youtube.com/watch?v=oP3c1h8v2ZQ – reference: DoddsPSClarkEMDesuSFrankMRReaganAJWilliamsJRMitchellLHarrisKDKloumannIMBagrowJPMegerdoomianKMcMahonMTTivnanBFDanforthCMHuman language reveals a universal positivity biasProc Natl Acad Sci USA201511282389239410.1073/pnas.1411678112 – reference: CampbellJThe hero with a thousand faces20083NovatoNew World Library – reference: UtherH-JThe types of international folktales. A classification and bibliography. Based on the system of Antti Aarne and Stith Thompson. Part I. Animal tales, tales of magic, religious tales, and realistic tales, with an introduction2011HelsinkiFinnish Academy of Science and Letters – reference: Winston PH (2011) The strong story hypothesis and the directed perception hypothesis – reference: DoddsPSHarrisKDKloumannIMBlissCADanforthCMTemporal patterns of happiness and information in a global social network: hedonometrics and TwitterPLoS ONE201161210.1371/journal.pone.0026752 – reference: GottschallJThe storytelling animal: how stories make us human2013New YorkMariner Books – reference: Tenenbaum DJ, Barrett K, Medaris SV, Devitt T (2015) In 10 languages, happy words beat sad ones. http://whyfiles.org/2015/in-10-languages-happy-words-beat-sad-ones/ – reference: NenkovaAMcKeownKA survey of text summarization techniquesMining text data2012BerlinSpringer437610.1007/978-1-4614-3223-4_3 – reference: MinSParkJNarrative as a complex network: a study of Victor Hugo’s Les MisérablesProceedings of HCI Korea2016 – reference: BexFJBench-CaponTJPersuasive stories for multi-agent argumentationAAAI fall symposium: computational models of narrative20104 – reference: Bost X, Labatut V, Linarès G (2016) Narrative smoothing: dynamic conversational network for the analysis of TV series plots. arXiv:1602.07811 – reference: Riedl MO, Harrison B (2015) Using stories to teach human values to artificial agents – reference: RibeiroFNAraújoMGonçalvesPGonçalvesMABenevenutoFSentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methodsEPJ Data Sci20165110.1140/epjds/s13688-016-0085-1 – reference: Various (2010) Project Gutenberg. http://gutenberg.org – reference: KohonenTThe self-organizing mapProc IEEE19907891464148010.1109/5.58325 – reference: LiBLee-UrbanSJohnstonGRiedlMStory generation with crowdsourced plot graphsProceedings of the twenty-seventh AAAI conference on artificial intelligence2013 – reference: NickersonRSConfirmation bias: a ubiquitous phenomenon in many guisesRev Gen Psychol1998217522010.1037/1089-2680.2.2.175 – reference: Jockers M (2014) A novel method for detecting plot. http://www.matthewjockers.net/2014/06/05/a-novel-method-for-detecting-plot/ – reference: WardJHJrHierarchical grouping to optimize an objective functionJ Am Stat Assoc19635830123624414818810.1080/01621459.1963.10500845 – reference: Dodds PS (2013) Homo narrativus and the trouble with fame. Nautilus magazine. http://nautil.us/issue/5/fame/homo-narrativus-and-the-trouble-with-fame – reference: DolbySKLiterary folkloristics and the personal narrative2008BloomingtonTrickster Press – reference: KirschenbaumMGThe remaking of reading: data mining and the digital humanitiesThe national science foundation symposium on next generation of data mining and cyber-enabled discovery for innovation2007 – reference: BookerCThe seven basic plots: why we tell stories2006New YorkBloomsbury Academic – reference: PratchettTStewartICohenJThe science of Discworld II: the globe2003LondonEbury Press – reference: Cave S (2013) The 4 stories we tell ourselves about death. http://www.ted.com/talks/stephen_cave_the_4_stories_we_tell_ourselves_about_death – reference: da SilvaSGTehraniJJComparative phylogenetic analyses uncover the ancient roots of Indo-European folktalesR Soc Open Sci20163110.1098/rsos.150645http://rsos.royalsocietypublishing.org/content/3/1/150645.full.pdf – reference: GleickJThe information: a history, a theory, a flood2011New YorkPantheon – reference: VonnegutKPalm sunday1981New YorkRosettaBooks LLC – reference: MacDonaldMRStorytellers sourcebook: a subject, title, and motif index to folklore collections for children1982Farmington HillsGale Group – reference: Prado SD, Dahmen SR, Bazzan ALC, Carron PM, Kenna R (2016) Temporal network analysis of literary texts. arXiv:1602.07275 – reference: Reagan A, Tivnan B, Williams JR, Danforth CM, Dodds PS (2015) Benchmarking sentiment analysis methods for large-scale texts: a case for using continuum-scored words and word shift graphs. arXiv:1512.00531 – reference: RousseeuwPJSilhouettes: a graphical aid to the interpretation and validation of cluster analysisJ Comput Appl Math198720536510.1016/0377-0427(87)90125-70636.62059 – reference: ProppVMorphology of the folktale (1928)1968AustinUniversity of Texas Press – reference: DundesAThe motif-index and the tale type index: a critiqueJ Folklore Res199734195202 – volume: 58 start-page: 236 issue: 301 year: 1963 ident: 93_CR26 publication-title: J Am Stat Assoc doi: 10.1080/01621459.1963.10500845 – volume: 34 start-page: 195 year: 1997 ident: 93_CR13 publication-title: J Folklore Res – ident: 93_CR32 – ident: 93_CR34 doi: 10.1142/S0219525916500053 – volume-title: Storytellers sourcebook: a subject, title, and motif index to folklore collections for children year: 1982 ident: 93_CR9 – volume-title: Literary folkloristics and the personal narrative year: 2008 ident: 93_CR14 – volume: 3 issue: 1 year: 2016 ident: 93_CR10 publication-title: R Soc Open Sci doi: 10.1098/rsos.150645 – ident: 93_CR37 – volume: 20 start-page: 53 year: 1987 ident: 93_CR29 publication-title: J Comput Appl Math doi: 10.1016/0377-0427(87)90125-7 – start-page: 43 volume-title: Mining text data year: 2012 ident: 93_CR35 doi: 10.1007/978-1-4614-3223-4_3 – ident: 93_CR23 – volume-title: The storytelling animal: how stories make us human year: 2013 ident: 93_CR3 – volume-title: The information: a history, a theory, a flood year: 2011 ident: 93_CR7 – ident: 93_CR4 – volume: 2 start-page: 175 year: 1998 ident: 93_CR6 publication-title: Rev Gen Psychol doi: 10.1037/1089-2680.2.2.175 – volume-title: Proceedings of the twenty-seventh AAAI conference on artificial intelligence year: 2013 ident: 93_CR30 – volume-title: The types of international folktales. A classification and bibliography. Based on the system of Antti Aarne and Stith Thompson. Part I. Animal tales, tales of magic, religious tales, and realistic tales, with an introduction year: 2011 ident: 93_CR15 – ident: 93_CR25 – volume: 5 issue: 1 year: 2016 ident: 93_CR21 publication-title: EPJ Data Sci doi: 10.1140/epjds/s13688-016-0085-1 – ident: 93_CR12 – volume-title: Palm sunday year: 1981 ident: 93_CR18 – volume: 78 start-page: 1464 issue: 9 year: 1990 ident: 93_CR27 publication-title: Proc IEEE doi: 10.1109/5.58325 – volume-title: The science of Discworld II: the globe year: 2003 ident: 93_CR1 – volume: 112 start-page: 2389 issue: 8 year: 2015 ident: 93_CR28 publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1411678112 – start-page: 4 volume-title: AAAI fall symposium: computational models of narrative year: 2010 ident: 93_CR31 – volume-title: The seven basic plots: why we tell stories year: 2006 ident: 93_CR24 – volume-title: Morphology of the folktale (1928) year: 1968 ident: 93_CR8 doi: 10.7560/783911 – ident: 93_CR19 – ident: 93_CR20 – volume: 6 issue: 12 year: 2011 ident: 93_CR22 publication-title: PLoS ONE doi: 10.1371/journal.pone.0026752 – volume-title: The hero with a thousand faces year: 2008 ident: 93_CR2 – ident: 93_CR36 – volume-title: The national science foundation symposium on next generation of data mining and cyber-enabled discovery for innovation year: 2007 ident: 93_CR16 – volume-title: Proceedings of HCI Korea year: 2016 ident: 93_CR11 – volume-title: Distant reading year: 2013 ident: 93_CR17 – ident: 93_CR5 – ident: 93_CR33 doi: 10.1109/ASONAM.2016.7752379 |
| SSID | ssj0001325366 |
| Score | 2.5157933 |
| Snippet | Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its texts using... Abstract Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture’s evolution through its... |
| SourceID | doaj proquest crossref springer |
| SourceType | Open Website Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 31 |
| SubjectTerms | Complexity Computer Appl. in Social and Behavioral Sciences Computer Science Data-driven Science Emotions language Modeling and Theory Building narratology Natural language processing Regular Article sentiment mining society stories Supervised learning Unsupervised learning |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV09T8MwELVQJxbEpygU5IEBhqhxbMfJhACBKiSYqNTNcvwhilBb4SLBv-cuSauWgS6siS1Z7865d875HSEXKatQ9YMnyoY8QZ3JxACxTipmIN6UEOQcHug_PeeDoXgcydFKqy-sCWvkgRvg-t6V1libBgUf0lIwIyGdM1UavLRVldbUCGLeSjJVn67wTPI8bwu6IIno-9mbi_3IeF5g9Rak0ZDLJ2wtHNWq_WtU89ff0TroPOySnZYt0ptmlXtky0_2yV67HyO9bEWjrw7INdib-qYnD8wA9410GmitAQIjzYenboplL8AwafVN4_iLQgQbWxpfzczHQzJ8uH-5GyRtc4TEAgWZA6LCMRUUq5R0EjMTJEdlsIAO4z41TFiuMl_aUGRGGSuxWstJ4x3gCCzliHQm04k_JrQoi1QE53nh8aKpAAth3hhKIb2ynHVJvsBI21Y5HBtYvOvmVnOqa3B1A67GmjEEV8PEdDlx1ohnbJ5yi0ZYDkf16_oB-IRufUJv8oku6S1MqNstGTUrcpkV2ICrS9jCrCuv_17XyX-s65RsZ-h6eCoteqQz__j0Z8Bp5tV57b4_RBvwqg priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Central dbid: BENPR link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV1LT9wwELZ4XHpB0IdYuq184FAO0dqJHTsnVBAIVSpCCCRuluNHAaHNst5K8O-ZSbw8eqDXxBNFM7bnm_H4G0J2GW-R9aMqlIt1gTyThQVgXbTcgr9pwMl5TOj_Pq1PLsWvK3mVE24pl1Uu98R-o_adwxz5hOtalhr7J-3P7gvsGoWnq7mFxipZhy1YQ_C1fnB0enb-kmWpSlnVdS7sgmBiEma3Pk0Sr2qNVVwQTkNMX_A3bqln738DOf85Je2dz_Em2ciokf4czLxFVsL0I9nK6zLRH5k8eu8T2Qe70zD05gEJmMaJdpH2XCAw0s4D9R2WvwDSpO0jTTcPFDzZjaPp2s5C-kwuj48uDk-K3CShcABFFqBZ4bmKirdKeokRCoKkJjqmLK8Cs1y4SpWhcVGXVlknsWrLSxu8Fg2glS9kbdpNwzahutFMRB8qHfDCqQBLYfwYGyGDchUfkXqpI-Mygzg2srgzw-1mZnrlmkG5BmvHULkGBNmz4Gwg0fi_yAEa4Xk4smD3D7r5H5MXlQm-cdY5FhU42UZwKyHUty2LQbq2ZXZExksTmrw0k3mZSCPCl2Z99fr9_9p5_5NfyYcSJxXmncWYrC3mf8M3QC2L9nuemk-PGegl priority: 102 providerName: ProQuest |
| Title | The emotional arcs of stories are dominated by six basic shapes |
| URI | https://link.springer.com/article/10.1140/epjds/s13688-016-0093-1 https://www.proquest.com/docview/1865288690 https://doaj.org/article/ed9cacc0f7284941a5907ab0fe5cbb0a |
| Volume | 5 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELZKe-ECfYBYaFc-9EAPUe3Ejp1TtV11qVaiQkCl3izHDyhCu6vNIsG_74zjVC2HInFJosQTRTPjzMPjbwg5ZrxF1I-qUC7WBeJMFhYc66LlFuxNA0bOY0L_41V9eS3mN_LmYasvrHYfliTTn7rHs2WnYfXDd6cdr2qN5VcQB0MwXkDgsyMhgEflnuaNDim9UpWyqutc0fUE_SN7lGD7H_mafy2PJqsz2yUvsrtIJ71898hWWOyTl0MrBppn5j7Zy1cdfZ-BpE8OyBnoAA19nx54Cah0R5eRJlwQGGnXgfollsKA10nbP7S7_U3Bqt062n23q9C9Itezi6_TyyI3TCgcuCUb4LLwXEXFWyW9xGgFHaYmOqYsrwKzXLhKlaFxUZdWWSexgstLG7wWDXgur8n2YrkIbwjVjWYi-lDpgJtPBUgNY8nYCBmUq_iI1APbjMto4tjU4qfpdzozk_hten4brCNDfhsgZPeEqx5Q498k5yiX--GIiJ1uLNffTJ5gJvjGWedYVGBwG8GthLDftiwG6dqW2RE5HKRq8jTtDNe1LDU25RoRPkj6weOnv-vtf9C8I89LVD5MTItDsr1Z_wpH4NZs2jF5pmcfxmRnMpl_mcP5_OLq0-dxUms81tNxShjcAVfw8-E |
| linkProvider | Springer Nature |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELaqcoALaguIpQV8AAkO0dqxndgHVAFl2dLHqZV6M44fpQhtls0i2j_V38hMHi3lUE69Jp7ImRnPjMfjbwh5xXiFqB8iK30qMsSZzBwE1lnFHfgbA04uYEL_4LCYHssvJ-pkhVwOd2GwrHKwia2hDrXHHPmY60LlGvsnbc9_Ztg1Ck9XhxYanVrsxYvfsGVr3u3ugHxf5_nk09HHadZ3Fcg8-O4lTEUGXqaSV6UKCkN6jCpM8qx0XETmuPSizKPxSeeudF5hmVNQLgYtjUbwJTD596QQBleUnny-zumIXImi6MvIYOsyjvPvoRk3XBQaa8Zg886AL_yGE2x7BdwIcP85k21d3WSNPOxjVPq-U6p1shJnG2S9twINfdNDVb99RLZBy2jsOgEBBXCnoXWiLfIIjHSLSEONxTYQ19LqgjZn5xT85pmnzTc3j81jcnwnzHtCVmf1LD4lVBvNZApR6IjXWyXoBe5Wk5Eqll7wESkGHlnf45Vj24wftrtLzWzLXNsx12KlGjLXAiG7Ipx3kB3_J_mAQrgajpjb7YN6cWr7JWxjMN55z1IJLt1I7pSBv65YispXFXMjsjWI0PaGoLHXajsifBDrX69vn9ez2z_5ktyfHh3s2_3dw71N8iBHBcOMt9wiq8vFr_gc4qVl9aJVUkq-3vWq-ANVjCMg |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELaqrYS4IMpDLBTwASQ4RGsndpwcUEUfq5bCqkJU6s04fkAR2izrRdC_xq_rTOK0lEM59Zp4Imc8npfH3xDygvEGUT-KTNlQZogzmRlwrLOGG7A3NRg5hwn9D7Ny_1i8O5Ena-TPcBcGyyoHndgpatdazJFPeFXKvML-SZOQyiKOdqdbix8ZdpDCk9ahnUYvIof-7BeEb_HNwS6s9cs8n-592tnPUoeBzIIdX8G0hOMqKN4o6SS69-hh1MEyZXjhmeHCFir3tQ1VbpSxEkuenDTeVaKuEIgJ1P-6gqiIjcj69t7s6ONlhqfIZVGWqagMApmJX3xzcRJ5UVZYQQahPAMu8SsmsesccMXd_eeEtjN807vkTvJY6dtexDbImp_fIxtJJ0T6KgFXv75PtkDmqO_7AgEF8CfSNtAOhwRGmqWnrsXSG_ByaXNG4-lvClb01NL41Sx8fECOb4R9D8lo3s79I0KrumIiOF9UHi-7CpASjF1DLaRXtuBjUg480jahl2MTje-6v1nNdMdc3TNXY90aMlcDIbsgXPQAHv8n2cZFuBiOCNzdg3b5RacNrb2rrbGWBQUGvhbcyBr-umHBS9s0zIzJ5rCEOqmFqC-FeEz4sKx_vb5-Xo-v_-Rzcgt2hH5_MDt8Qm7nKF-Y_habZLRa_vRPwXlaNc-SlFLy-aY3xjnjMiiy |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+emotional+arcs+of+stories+are+dominated+by+six+basic+shapes&rft.jtitle=EPJ+data+science&rft.au=Reagan%2C+Andrew+J&rft.au=Mitchell%2C+Lewis&rft.au=Kiley%2C+Dilan&rft.au=Danforth%2C+Christopher+M&rft.date=2016-11-04&rft.pub=Springer+Berlin+Heidelberg&rft.eissn=2193-1127&rft.volume=5&rft.issue=1&rft_id=info:doi/10.1140%2Fepjds%2Fs13688-016-0093-1&rft.externalDocID=10_1140_epjds_s13688_016_0093_1 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2193-1127&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2193-1127&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2193-1127&client=summon |