A New Web-Based Big Data Analytics for Dynamic Public Opinion Mapping in Digital Networks on Contested Biotechnology Fields
The expression “public opinion” has long been part of common parlance. However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of p...
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Veröffentlicht in: | Omics (Larchmont, N.Y.) N.Y.), 2020-01, Vol.24 (1), p.29-42 |
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description | The expression “public opinion” has long been part of common parlance. However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of public opinion, let alone on how to measure it. This study reports on the usefulness of web-based big data digital network analytics in deciphering the distributed meanings and sense making related to controversial biotechnology applications. Using stem cell therapies as a case study, we argue that such digital network analysis can complement the traditional opinion polls while avoiding the sampling bias that is typical of opinion polls. Although the polls cannot account for the opinion dynamics, combining them with web-based big data analysis can shed light on three dimensions of public opinion essential for sense making: counts or volume of opinion data, content, and movement of opinions. This approach is particularly promising in the case of ongoing scientific controversies that increasingly overflow into the public sphere morphing into public political debates. In particular, our study focuses as a case study on public controversies over the clinical provision of stem cell therapies. Using web entities specifically addressing stem cell issues, including their dynamic aggregation, the internal architecture of the web corpus we report in this study brings the third dimension of public opinion (movement) into sharper focus. Notably, the corpus of stem cell networks through web connectivity presents hot spots of distributed meaning. Large-scale surveys conducted on these issues, such as the Eurobarometer of Biotechnology, reveal that European citizens only accept research on stem cells if they are highly regulated, while the stem cell digital network analysis presented in this study suggests that distributed meaning is promise centeredness. Although major scientific journals and companies tend to structure public opinion networks, our finding of promise centeredness as a key ingredient of distributed meaning and sense making is consistent with therapeutic tourism that remains as an important facet of the stem cell community despite the lack of material standards. This new approach to digital network analysis has crosscutting corollaries for rethinking the notion of public opinion, be it in electoral preferences or as we discuss in this study, for new ways to meas |
doi_str_mv | 10.1089/omi.2019.0130 |
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However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of public opinion, let alone on how to measure it. This study reports on the usefulness of web-based big data digital network analytics in deciphering the distributed meanings and sense making related to controversial biotechnology applications. Using stem cell therapies as a case study, we argue that such digital network analysis can complement the traditional opinion polls while avoiding the sampling bias that is typical of opinion polls. Although the polls cannot account for the opinion dynamics, combining them with web-based big data analysis can shed light on three dimensions of public opinion essential for sense making: counts or volume of opinion data, content, and movement of opinions. This approach is particularly promising in the case of ongoing scientific controversies that increasingly overflow into the public sphere morphing into public political debates. In particular, our study focuses as a case study on public controversies over the clinical provision of stem cell therapies. Using web entities specifically addressing stem cell issues, including their dynamic aggregation, the internal architecture of the web corpus we report in this study brings the third dimension of public opinion (movement) into sharper focus. Notably, the corpus of stem cell networks through web connectivity presents hot spots of distributed meaning. Large-scale surveys conducted on these issues, such as the Eurobarometer of Biotechnology, reveal that European citizens only accept research on stem cells if they are highly regulated, while the stem cell digital network analysis presented in this study suggests that distributed meaning is promise centeredness. Although major scientific journals and companies tend to structure public opinion networks, our finding of promise centeredness as a key ingredient of distributed meaning and sense making is consistent with therapeutic tourism that remains as an important facet of the stem cell community despite the lack of material standards. 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However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of public opinion, let alone on how to measure it. This study reports on the usefulness of web-based big data digital network analytics in deciphering the distributed meanings and sense making related to controversial biotechnology applications. Using stem cell therapies as a case study, we argue that such digital network analysis can complement the traditional opinion polls while avoiding the sampling bias that is typical of opinion polls. Although the polls cannot account for the opinion dynamics, combining them with web-based big data analysis can shed light on three dimensions of public opinion essential for sense making: counts or volume of opinion data, content, and movement of opinions. This approach is particularly promising in the case of ongoing scientific controversies that increasingly overflow into the public sphere morphing into public political debates. In particular, our study focuses as a case study on public controversies over the clinical provision of stem cell therapies. Using web entities specifically addressing stem cell issues, including their dynamic aggregation, the internal architecture of the web corpus we report in this study brings the third dimension of public opinion (movement) into sharper focus. Notably, the corpus of stem cell networks through web connectivity presents hot spots of distributed meaning. Large-scale surveys conducted on these issues, such as the Eurobarometer of Biotechnology, reveal that European citizens only accept research on stem cells if they are highly regulated, while the stem cell digital network analysis presented in this study suggests that distributed meaning is promise centeredness. Although major scientific journals and companies tend to structure public opinion networks, our finding of promise centeredness as a key ingredient of distributed meaning and sense making is consistent with therapeutic tourism that remains as an important facet of the stem cell community despite the lack of material standards. This new approach to digital network analysis has crosscutting corollaries for rethinking the notion of public opinion, be it in electoral preferences or as we discuss in this study, for new ways to measure, monitor, and democratically govern emerging technologies.</description><subject>Biotechnology & Applied Microbiology</subject><subject>Genetics & Heredity</subject><subject>Life Sciences & Biomedicine</subject><subject>Science & Technology</subject><issn>1536-2310</issn><issn>1557-8100</issn><issn>1557-8100</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>AOWDO</sourceid><sourceid>ARHDP</sourceid><recordid>eNqNkE2P0zAQhi0EYj_gyBX5iIRSZuwkdo_dlF2QFpYDiGPkOE4xOHaJHVUVfx6HLnuFgzUjzTOvxg8hLxBWCHL9Jox2xQDXK0AOj8g5VpUoJAI8XnpeF4wjnJGLGL8DMKwZf0rOOFawhro-J7829KM50K-mK65UND29sju6VUnRjVfumKyOdAgT3R69Gq2mn-bO5XK3t94GTz-ofe521Hq6tTublMtx6RCmH5HmcRN8MjH9iQ3J6G8-uLA70mtrXB-fkSeDctE8v6-X5Mv128_Nu-L27uZ9s7ktNOciFYMSiLVmvDRM9yz_QCkBXV-tByU1Q2mqumda1xLLoev7_LDmnVBMcYFa80vy6pS7n8LPOd_TjjZq45zyJsyxZUxKgYyVIqPFCdVTiHEyQ7uf7KimY4vQLr7b7LtdfLeL78y_vI-eu9H0D_RfwRmQJ-BgujBEbY3X5gEDgFJWpZAid4BNFpiy1ibMPuXV1_-_mml-opep8t5Z05kp_eP-3-kxrh8</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Tournay, Virginie</creator><creator>Jacomy, Mathieu</creator><creator>Necula, Andra</creator><creator>Leibing, Annette</creator><creator>Blasimme, Alessandro</creator><general>Mary Ann Liebert, Inc., publishers</general><general>Mary Ann Liebert, Inc</general><scope>17B</scope><scope>AOWDO</scope><scope>ARHDP</scope><scope>BLEPL</scope><scope>DTL</scope><scope>DVR</scope><scope>EGQ</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5908-2002</orcidid><orcidid>https://orcid.org/0000-0002-6417-6895</orcidid></search><sort><creationdate>20200101</creationdate><title>A New Web-Based Big Data Analytics for Dynamic Public Opinion Mapping in Digital Networks on Contested Biotechnology Fields</title><author>Tournay, Virginie ; Jacomy, Mathieu ; Necula, Andra ; Leibing, Annette ; Blasimme, Alessandro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-fa7116c234e2cd2623aa70bd59fa8c218e56d2cc6814fbddfbd163b7a2a371cc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biotechnology & Applied Microbiology</topic><topic>Genetics & Heredity</topic><topic>Life Sciences & Biomedicine</topic><topic>Science & Technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tournay, Virginie</creatorcontrib><creatorcontrib>Jacomy, Mathieu</creatorcontrib><creatorcontrib>Necula, Andra</creatorcontrib><creatorcontrib>Leibing, Annette</creatorcontrib><creatorcontrib>Blasimme, Alessandro</creatorcontrib><collection>Web of Knowledge</collection><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science - Social Sciences Citation Index – 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Social Sciences Citation Index</collection><collection>Web of Science Primary (SCIE, SSCI & AHCI)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Omics (Larchmont, N.Y.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tournay, Virginie</au><au>Jacomy, Mathieu</au><au>Necula, Andra</au><au>Leibing, Annette</au><au>Blasimme, Alessandro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A New Web-Based Big Data Analytics for Dynamic Public Opinion Mapping in Digital Networks on Contested Biotechnology Fields</atitle><jtitle>Omics (Larchmont, N.Y.)</jtitle><stitle>OMICS</stitle><addtitle>OMICS</addtitle><date>2020-01-01</date><risdate>2020</risdate><volume>24</volume><issue>1</issue><spage>29</spage><epage>42</epage><pages>29-42</pages><issn>1536-2310</issn><issn>1557-8100</issn><eissn>1557-8100</eissn><abstract>The expression “public opinion” has long been part of common parlance. However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of public opinion, let alone on how to measure it. This study reports on the usefulness of web-based big data digital network analytics in deciphering the distributed meanings and sense making related to controversial biotechnology applications. Using stem cell therapies as a case study, we argue that such digital network analysis can complement the traditional opinion polls while avoiding the sampling bias that is typical of opinion polls. Although the polls cannot account for the opinion dynamics, combining them with web-based big data analysis can shed light on three dimensions of public opinion essential for sense making: counts or volume of opinion data, content, and movement of opinions. This approach is particularly promising in the case of ongoing scientific controversies that increasingly overflow into the public sphere morphing into public political debates. In particular, our study focuses as a case study on public controversies over the clinical provision of stem cell therapies. Using web entities specifically addressing stem cell issues, including their dynamic aggregation, the internal architecture of the web corpus we report in this study brings the third dimension of public opinion (movement) into sharper focus. Notably, the corpus of stem cell networks through web connectivity presents hot spots of distributed meaning. Large-scale surveys conducted on these issues, such as the Eurobarometer of Biotechnology, reveal that European citizens only accept research on stem cells if they are highly regulated, while the stem cell digital network analysis presented in this study suggests that distributed meaning is promise centeredness. Although major scientific journals and companies tend to structure public opinion networks, our finding of promise centeredness as a key ingredient of distributed meaning and sense making is consistent with therapeutic tourism that remains as an important facet of the stem cell community despite the lack of material standards. This new approach to digital network analysis has crosscutting corollaries for rethinking the notion of public opinion, be it in electoral preferences or as we discuss in this study, for new ways to measure, monitor, and democratically govern emerging technologies.</abstract><cop>NEW ROCHELLE</cop><pub>Mary Ann Liebert, Inc., publishers</pub><pmid>31509066</pmid><doi>10.1089/omi.2019.0130</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-5908-2002</orcidid><orcidid>https://orcid.org/0000-0002-6417-6895</orcidid></addata></record> |
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subjects | Biotechnology & Applied Microbiology Genetics & Heredity Life Sciences & Biomedicine Science & Technology |
title | A New Web-Based Big Data Analytics for Dynamic Public Opinion Mapping in Digital Networks on Contested Biotechnology Fields |
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