Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013
BackgroundIn May 2013, a measles outbreak began in the Netherlands among Orthodox Protestants who often refuse vaccination for religious reasons. ObjectiveOur aim was to compare the number of messages expressed on Twitter and other social media during the measles outbreak with the number...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2015-05-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | http://www.jmir.org/2015/5/e128/ |
| _version_ | 1818405572112809984 |
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| author | Mollema, Liesbeth Harmsen, Irene Anhai Broekhuizen, Emma Clijnk, Rutger De Melker, Hester Paulussen, Theo Kok, Gerjo Ruiter, Robert Das, Enny |
| author_facet | Mollema, Liesbeth Harmsen, Irene Anhai Broekhuizen, Emma Clijnk, Rutger De Melker, Hester Paulussen, Theo Kok, Gerjo Ruiter, Robert Das, Enny |
| author_sort | Mollema, Liesbeth |
| collection | DOAJ |
| description | BackgroundIn May 2013, a measles outbreak began in the Netherlands among Orthodox Protestants who often refuse vaccination for religious reasons.
ObjectiveOur aim was to compare the number of messages expressed on Twitter and other social media during the measles outbreak with the number of online news articles and the number of reported measles cases to answer the question if and when social media reflect public opinion patterns versus disease patterns.
MethodsWe analyzed measles-related tweets, other social media messages, and online newspaper articles over a 7-month period (April 15 to November 11, 2013) with regard to topic and sentiment. Thematic analysis was used to structure and analyze the topics.
ResultsThere was a stronger correlation between the weekly number of social media messages and the weekly number of online news articles (P<.001 for both tweets and other social media messages) than between the weekly number of social media messages and the weekly number of reported measles cases (P=.003 and P=.048 for tweets and other social media messages, respectively), especially after the summer break. All data sources showed 3 large peaks, possibly triggered by announcements about the measles outbreak by the Dutch National Institute for Public Health and the Environment and statements made by well-known politicians. Most messages informed the public about the measles outbreak (ie, about the number of measles cases) (93/165, 56.4%) followed by messages about preventive measures taken to control the measles spread (47/132, 35.6%). The leading opinion expressed was frustration regarding people who do not vaccinate because of religious reasons (42/88, 48%).
ConclusionsThe monitoring of online (social) media might be useful for improving communication policies aiming to preserve vaccination acceptability among the general public. Data extracted from online (social) media provide insight into the opinions that are at a certain moment salient among the public, which enables public health institutes to respond immediately and appropriately to those public concerns. More research is required to develop an automatic coding system that captures content and user’s characteristics that are most relevant to the diseases within the National Immunization Program and related public health events and can inform official responses. |
| first_indexed | 2024-12-14T08:58:10Z |
| format | Article |
| id | doaj.art-1c1ebfbe0a1f4b6b8afe179c8fa1662b |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-12-14T08:58:10Z |
| publishDate | 2015-05-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-1c1ebfbe0a1f4b6b8afe179c8fa1662b2022-12-21T23:08:52ZengJMIR PublicationsJournal of Medical Internet Research1438-88712015-05-01175e12810.2196/jmir.3863Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013Mollema, LiesbethHarmsen, Irene AnhaiBroekhuizen, EmmaClijnk, RutgerDe Melker, HesterPaulussen, TheoKok, GerjoRuiter, RobertDas, EnnyBackgroundIn May 2013, a measles outbreak began in the Netherlands among Orthodox Protestants who often refuse vaccination for religious reasons. ObjectiveOur aim was to compare the number of messages expressed on Twitter and other social media during the measles outbreak with the number of online news articles and the number of reported measles cases to answer the question if and when social media reflect public opinion patterns versus disease patterns. MethodsWe analyzed measles-related tweets, other social media messages, and online newspaper articles over a 7-month period (April 15 to November 11, 2013) with regard to topic and sentiment. Thematic analysis was used to structure and analyze the topics. ResultsThere was a stronger correlation between the weekly number of social media messages and the weekly number of online news articles (P<.001 for both tweets and other social media messages) than between the weekly number of social media messages and the weekly number of reported measles cases (P=.003 and P=.048 for tweets and other social media messages, respectively), especially after the summer break. All data sources showed 3 large peaks, possibly triggered by announcements about the measles outbreak by the Dutch National Institute for Public Health and the Environment and statements made by well-known politicians. Most messages informed the public about the measles outbreak (ie, about the number of measles cases) (93/165, 56.4%) followed by messages about preventive measures taken to control the measles spread (47/132, 35.6%). The leading opinion expressed was frustration regarding people who do not vaccinate because of religious reasons (42/88, 48%). ConclusionsThe monitoring of online (social) media might be useful for improving communication policies aiming to preserve vaccination acceptability among the general public. Data extracted from online (social) media provide insight into the opinions that are at a certain moment salient among the public, which enables public health institutes to respond immediately and appropriately to those public concerns. More research is required to develop an automatic coding system that captures content and user’s characteristics that are most relevant to the diseases within the National Immunization Program and related public health events and can inform official responses.http://www.jmir.org/2015/5/e128/ |
| spellingShingle | Mollema, Liesbeth Harmsen, Irene Anhai Broekhuizen, Emma Clijnk, Rutger De Melker, Hester Paulussen, Theo Kok, Gerjo Ruiter, Robert Das, Enny Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 Journal of Medical Internet Research |
| title | Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 |
| title_full | Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 |
| title_fullStr | Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 |
| title_full_unstemmed | Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 |
| title_short | Disease Detection or Public Opinion Reflection? Content Analysis of Tweets, Other Social Media, and Online Newspapers During the Measles Outbreak in the Netherlands in 2013 |
| title_sort | disease detection or public opinion reflection content analysis of tweets other social media and online newspapers during the measles outbreak in the netherlands in 2013 |
| url | http://www.jmir.org/2015/5/e128/ |
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