author_facet Helles, Rasmus
Helles, Rasmus
author Helles, Rasmus
spellingShingle Helles, Rasmus
First Monday
The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
Computer Networks and Communications
Human-Computer Interaction
author_sort helles, rasmus
spelling Helles, Rasmus 1396-0466 University of Illinois Libraries Computer Networks and Communications Human-Computer Interaction http://dx.doi.org/10.5210/fm.v18i10.4874 <jats:p>This paper discusses how the advent of big data challenges established theories in Internet studies to redevelop existing explanatory strategies in order to incorporate the possibilities offered by this new empirical resource. The article suggests that established analytical procedures and theoretical frameworks used in Internet studies can be fruitfully employed to explain high–level structural phenomena that are only observable through the use of big data. The present article exemplifies this by offering a detailed analysis of how genre analysis of Web sites may be used to shed light on the generative mechanism behind the long–tail distribution of Web site use. The analysis shows that the long tail should be seen as a tiered version of popular top sites, and argues that downsizing of large–scale datasets in combination with qualitative and/or small–scale quantitative procedures may provide qualitatively better understandings of macro phenomena than purely automated, quantitative approaches.</jats:p> The big head and the long tail: An illustration of explanatory strategies for big data Internet studies First Monday
doi_str_mv 10.5210/fm.v18i10.4874
facet_avail Online
Free
finc_class_facet Informatik
format ElectronicArticle
fullrecord blob:ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuNTIxMC9mbS52MThpMTAuNDg3NA
id ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuNTIxMC9mbS52MThpMTAuNDg3NA
institution DE-14
FID-BBI-DE-23
DE-105
DE-Ch1
DE-L229
DE-D275
DE-Bn3
DE-Brt1
DE-Zwi2
DE-D161
DE-Zi4
DE-Gla1
DE-15
DE-Pl11
DE-Rs1
FID-MEDIEN-DE-15
imprint University of Illinois Libraries, 2013
imprint_str_mv University of Illinois Libraries, 2013
issn 1396-0466
issn_str_mv 1396-0466
language Undetermined
mega_collection University of Illinois Libraries (CrossRef)
match_str helles2013thebigheadandthelongtailanillustrationofexplanatorystrategiesforbigdatainternetstudies
publishDateSort 2013
publisher University of Illinois Libraries
recordtype ai
record_format ai
series First Monday
source_id 49
title The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_unstemmed The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_full The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_fullStr The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_full_unstemmed The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_short The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_sort the big head and the long tail: an illustration of explanatory strategies for big data internet studies
topic Computer Networks and Communications
Human-Computer Interaction
url http://dx.doi.org/10.5210/fm.v18i10.4874
publishDate 2013
physical
description <jats:p>This paper discusses how the advent of big data challenges established theories in Internet studies to redevelop existing explanatory strategies in order to incorporate the possibilities offered by this new empirical resource. The article suggests that established analytical procedures and theoretical frameworks used in Internet studies can be fruitfully employed to explain high–level structural phenomena that are only observable through the use of big data. The present article exemplifies this by offering a detailed analysis of how genre analysis of Web sites may be used to shed light on the generative mechanism behind the long–tail distribution of Web site use. The analysis shows that the long tail should be seen as a tiered version of popular top sites, and argues that downsizing of large–scale datasets in combination with qualitative and/or small–scale quantitative procedures may provide qualitatively better understandings of macro phenomena than purely automated, quantitative approaches.</jats:p>
container_start_page 0
container_title First Monday
format_de105 Article, E-Article
format_de14 Article, E-Article
format_de15 Article, E-Article
format_de520 Article, E-Article
format_de540 Article, E-Article
format_dech1 Article, E-Article
format_ded117 Article, E-Article
format_degla1 E-Article
format_del152 Buch
format_del189 Article, E-Article
format_dezi4 Article
format_dezwi2 Article, E-Article
format_finc Article, E-Article
format_nrw Article, E-Article
_version_ 1792331882929586177
geogr_code not assigned
last_indexed 2024-03-01T13:47:43.546Z
geogr_code_person not assigned
openURL url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fvufind.svn.sourceforge.net%3Agenerator&rft.title=The+big+head+and+the+long+tail%3A+An+illustration+of+explanatory+strategies+for+big+data+Internet+studies&rft.date=2013-09-30&genre=article&issn=1396-0466&jtitle=First+Monday&atitle=The+big+head+and+the+long+tail%3A+An+illustration+of+explanatory+strategies+for+big+data+Internet+studies&aulast=Helles&aufirst=Rasmus&rft_id=info%3Adoi%2F10.5210%2Ffm.v18i10.4874&rft.language%5B0%5D=und
SOLR
_version_ 1792331882929586177
author Helles, Rasmus
author_facet Helles, Rasmus, Helles, Rasmus
author_sort helles, rasmus
container_start_page 0
container_title First Monday
description <jats:p>This paper discusses how the advent of big data challenges established theories in Internet studies to redevelop existing explanatory strategies in order to incorporate the possibilities offered by this new empirical resource. The article suggests that established analytical procedures and theoretical frameworks used in Internet studies can be fruitfully employed to explain high–level structural phenomena that are only observable through the use of big data. The present article exemplifies this by offering a detailed analysis of how genre analysis of Web sites may be used to shed light on the generative mechanism behind the long–tail distribution of Web site use. The analysis shows that the long tail should be seen as a tiered version of popular top sites, and argues that downsizing of large–scale datasets in combination with qualitative and/or small–scale quantitative procedures may provide qualitatively better understandings of macro phenomena than purely automated, quantitative approaches.</jats:p>
doi_str_mv 10.5210/fm.v18i10.4874
facet_avail Online, Free
finc_class_facet Informatik
format ElectronicArticle
format_de105 Article, E-Article
format_de14 Article, E-Article
format_de15 Article, E-Article
format_de520 Article, E-Article
format_de540 Article, E-Article
format_dech1 Article, E-Article
format_ded117 Article, E-Article
format_degla1 E-Article
format_del152 Buch
format_del189 Article, E-Article
format_dezi4 Article
format_dezwi2 Article, E-Article
format_finc Article, E-Article
format_nrw Article, E-Article
geogr_code not assigned
geogr_code_person not assigned
id ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuNTIxMC9mbS52MThpMTAuNDg3NA
imprint University of Illinois Libraries, 2013
imprint_str_mv University of Illinois Libraries, 2013
institution DE-14, FID-BBI-DE-23, DE-105, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161, DE-Zi4, DE-Gla1, DE-15, DE-Pl11, DE-Rs1, FID-MEDIEN-DE-15
issn 1396-0466
issn_str_mv 1396-0466
language Undetermined
last_indexed 2024-03-01T13:47:43.546Z
match_str helles2013thebigheadandthelongtailanillustrationofexplanatorystrategiesforbigdatainternetstudies
mega_collection University of Illinois Libraries (CrossRef)
physical
publishDate 2013
publishDateSort 2013
publisher University of Illinois Libraries
record_format ai
recordtype ai
series First Monday
source_id 49
spelling Helles, Rasmus 1396-0466 University of Illinois Libraries Computer Networks and Communications Human-Computer Interaction http://dx.doi.org/10.5210/fm.v18i10.4874 <jats:p>This paper discusses how the advent of big data challenges established theories in Internet studies to redevelop existing explanatory strategies in order to incorporate the possibilities offered by this new empirical resource. The article suggests that established analytical procedures and theoretical frameworks used in Internet studies can be fruitfully employed to explain high–level structural phenomena that are only observable through the use of big data. The present article exemplifies this by offering a detailed analysis of how genre analysis of Web sites may be used to shed light on the generative mechanism behind the long–tail distribution of Web site use. The analysis shows that the long tail should be seen as a tiered version of popular top sites, and argues that downsizing of large–scale datasets in combination with qualitative and/or small–scale quantitative procedures may provide qualitatively better understandings of macro phenomena than purely automated, quantitative approaches.</jats:p> The big head and the long tail: An illustration of explanatory strategies for big data Internet studies First Monday
spellingShingle Helles, Rasmus, First Monday, The big head and the long tail: An illustration of explanatory strategies for big data Internet studies, Computer Networks and Communications, Human-Computer Interaction
title The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_full The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_fullStr The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_full_unstemmed The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_short The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
title_sort the big head and the long tail: an illustration of explanatory strategies for big data internet studies
title_unstemmed The big head and the long tail: An illustration of explanatory strategies for big data Internet studies
topic Computer Networks and Communications, Human-Computer Interaction
url http://dx.doi.org/10.5210/fm.v18i10.4874