Social media analytics and reachability evaluation - #Diabetes
Diabetes as a lifestyle disorder could be effectively managed by creating awareness among people through social media. Understanding the content of Twitter messages will aid in strategizing health communication about diabetes to the community through Twitter. This study aimed to analyze the content,...
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Veröffentlicht in: | Diabetes & metabolic syndrome clinical research & reviews 2022-01, Vol.16 (1), p.102359-102359, Article 102359 |
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creator | Karmegam, Dhivya Mappillairaju, Bagavandas |
description | Diabetes as a lifestyle disorder could be effectively managed by creating awareness among people through social media. Understanding the content of Twitter messages will aid in strategizing health communication about diabetes to the community through Twitter. This study aimed to analyze the content, sentiment, and reachability of diabetes related tweets posted in India.
Diabetes related messages from India were collected via Twitter's Application Programming Interface for April 2019. Themes and subthemes of tweet content were identified from randomly selected tweets. The tweets were coded as the source, themes, and subthemes manually. Sentiment analysis of the tweets was done by a lexicon-based approach. The reachability of tweets was assessed based on re-tweet and favorite counts.
Out of 1840 tweets, 57.28% were from organizations and 42.72% were from individuals. The largest proportion of tweet messages were informative (50.76%), followed by promotional tweets (21.52%). The largest proportion of tweets were positive (40.4%) followed by neutral (31.14%) tweets. Among the six major themes, the diabetes story had the highest reachability.
The outcome of this study would aid public health professionals in planning information dissemination and communication regarding diabetes on Twitter so that the right information reaches a wider population.
•In India, People seek guidance and medical support regarding diabetes from social media.•Messages posted by individuals, personal experiences with positive sentiment had higher reachability in Twitter.•Performing content analysis of tweets helped in understanding the need and opinion of people regarding diabetes.•Organizations were active in posting tweets, but they didn't take full advantage of communicating features in social media. |
doi_str_mv | 10.1016/j.dsx.2021.102359 |
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Diabetes related messages from India were collected via Twitter's Application Programming Interface for April 2019. Themes and subthemes of tweet content were identified from randomly selected tweets. The tweets were coded as the source, themes, and subthemes manually. Sentiment analysis of the tweets was done by a lexicon-based approach. The reachability of tweets was assessed based on re-tweet and favorite counts.
Out of 1840 tweets, 57.28% were from organizations and 42.72% were from individuals. The largest proportion of tweet messages were informative (50.76%), followed by promotional tweets (21.52%). The largest proportion of tweets were positive (40.4%) followed by neutral (31.14%) tweets. Among the six major themes, the diabetes story had the highest reachability.
The outcome of this study would aid public health professionals in planning information dissemination and communication regarding diabetes on Twitter so that the right information reaches a wider population.
•In India, People seek guidance and medical support regarding diabetes from social media.•Messages posted by individuals, personal experiences with positive sentiment had higher reachability in Twitter.•Performing content analysis of tweets helped in understanding the need and opinion of people regarding diabetes.•Organizations were active in posting tweets, but they didn't take full advantage of communicating features in social media.</description><identifier>ISSN: 1871-4021</identifier><identifier>EISSN: 1878-0334</identifier><identifier>DOI: 10.1016/j.dsx.2021.102359</identifier><identifier>PMID: 34920205</identifier><language>eng</language><publisher>Netherlands: Elsevier Ltd</publisher><subject>Content analysis ; Diabetes ; Diabetes Mellitus - diagnosis ; Diabetes Mellitus - epidemiology ; Health Communication ; Humans ; India - epidemiology ; Public Health ; Reachability evaluation ; Social Media ; Twitter</subject><ispartof>Diabetes & metabolic syndrome clinical research & reviews, 2022-01, Vol.16 (1), p.102359-102359, Article 102359</ispartof><rights>2021 Diabetes India</rights><rights>Copyright © 2021 Diabetes India. Published by Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-9a3e10f623d658579f22c3aba5adf1b5f65dc3b6ee4d80e08eccce9784d0c5c3</citedby><cites>FETCH-LOGICAL-c353t-9a3e10f623d658579f22c3aba5adf1b5f65dc3b6ee4d80e08eccce9784d0c5c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1871402121003799$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34920205$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Karmegam, Dhivya</creatorcontrib><creatorcontrib>Mappillairaju, Bagavandas</creatorcontrib><title>Social media analytics and reachability evaluation - #Diabetes</title><title>Diabetes & metabolic syndrome clinical research & reviews</title><addtitle>Diabetes Metab Syndr</addtitle><description>Diabetes as a lifestyle disorder could be effectively managed by creating awareness among people through social media. Understanding the content of Twitter messages will aid in strategizing health communication about diabetes to the community through Twitter. This study aimed to analyze the content, sentiment, and reachability of diabetes related tweets posted in India.
Diabetes related messages from India were collected via Twitter's Application Programming Interface for April 2019. Themes and subthemes of tweet content were identified from randomly selected tweets. The tweets were coded as the source, themes, and subthemes manually. Sentiment analysis of the tweets was done by a lexicon-based approach. The reachability of tweets was assessed based on re-tweet and favorite counts.
Out of 1840 tweets, 57.28% were from organizations and 42.72% were from individuals. The largest proportion of tweet messages were informative (50.76%), followed by promotional tweets (21.52%). The largest proportion of tweets were positive (40.4%) followed by neutral (31.14%) tweets. Among the six major themes, the diabetes story had the highest reachability.
The outcome of this study would aid public health professionals in planning information dissemination and communication regarding diabetes on Twitter so that the right information reaches a wider population.
•In India, People seek guidance and medical support regarding diabetes from social media.•Messages posted by individuals, personal experiences with positive sentiment had higher reachability in Twitter.•Performing content analysis of tweets helped in understanding the need and opinion of people regarding diabetes.•Organizations were active in posting tweets, but they didn't take full advantage of communicating features in social media.</description><subject>Content analysis</subject><subject>Diabetes</subject><subject>Diabetes Mellitus - diagnosis</subject><subject>Diabetes Mellitus - epidemiology</subject><subject>Health Communication</subject><subject>Humans</subject><subject>India - epidemiology</subject><subject>Public Health</subject><subject>Reachability evaluation</subject><subject>Social Media</subject><subject>Twitter</subject><issn>1871-4021</issn><issn>1878-0334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM1Lw0AQxRdRrFb_AC8S8OIldT-y-UAQpH5CwYO9L5PZCW5Jk5pNiv3v3drq0dO8Yd57MD_GLgSfCC7Sm8XE-q-J5FKEXSpdHLATkWd5zJVKDn-0iJNwHrFT7xeca13I4piNVFKEFNcn7O69RQd1tCTrIIIG6k3v0Adlo44AP6B0tes3Ea2hHqB3bRPF0dWDg5J68mfsqILa0_l-jtn86XE-fYlnb8-v0_tZjEqrPi5AkeBVKpVNda6zopISFZSgwVai1FWqLaoyJUpszonnhIhUZHliOWpUY3a9q1117edAvjdL55HqGhpqB29kKkSqMy1VsIqdFbvW-44qs-rcErqNEdxsqZmFCdTMlprZUQuZy339UAYQf4lfTMFwuzNQ-HHtqDMeHTUYoHWEvbGt-6f-G-YsfL8</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Karmegam, Dhivya</creator><creator>Mappillairaju, Bagavandas</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202201</creationdate><title>Social media analytics and reachability evaluation - #Diabetes</title><author>Karmegam, Dhivya ; Mappillairaju, Bagavandas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-9a3e10f623d658579f22c3aba5adf1b5f65dc3b6ee4d80e08eccce9784d0c5c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Content analysis</topic><topic>Diabetes</topic><topic>Diabetes Mellitus - diagnosis</topic><topic>Diabetes Mellitus - epidemiology</topic><topic>Health Communication</topic><topic>Humans</topic><topic>India - epidemiology</topic><topic>Public Health</topic><topic>Reachability evaluation</topic><topic>Social Media</topic><topic>Twitter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Karmegam, Dhivya</creatorcontrib><creatorcontrib>Mappillairaju, Bagavandas</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Diabetes & metabolic syndrome clinical research & reviews</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Karmegam, Dhivya</au><au>Mappillairaju, Bagavandas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Social media analytics and reachability evaluation - #Diabetes</atitle><jtitle>Diabetes & metabolic syndrome clinical research & reviews</jtitle><addtitle>Diabetes Metab Syndr</addtitle><date>2022-01</date><risdate>2022</risdate><volume>16</volume><issue>1</issue><spage>102359</spage><epage>102359</epage><pages>102359-102359</pages><artnum>102359</artnum><issn>1871-4021</issn><eissn>1878-0334</eissn><abstract>Diabetes as a lifestyle disorder could be effectively managed by creating awareness among people through social media. Understanding the content of Twitter messages will aid in strategizing health communication about diabetes to the community through Twitter. This study aimed to analyze the content, sentiment, and reachability of diabetes related tweets posted in India.
Diabetes related messages from India were collected via Twitter's Application Programming Interface for April 2019. Themes and subthemes of tweet content were identified from randomly selected tweets. The tweets were coded as the source, themes, and subthemes manually. Sentiment analysis of the tweets was done by a lexicon-based approach. The reachability of tweets was assessed based on re-tweet and favorite counts.
Out of 1840 tweets, 57.28% were from organizations and 42.72% were from individuals. The largest proportion of tweet messages were informative (50.76%), followed by promotional tweets (21.52%). The largest proportion of tweets were positive (40.4%) followed by neutral (31.14%) tweets. Among the six major themes, the diabetes story had the highest reachability.
The outcome of this study would aid public health professionals in planning information dissemination and communication regarding diabetes on Twitter so that the right information reaches a wider population.
•In India, People seek guidance and medical support regarding diabetes from social media.•Messages posted by individuals, personal experiences with positive sentiment had higher reachability in Twitter.•Performing content analysis of tweets helped in understanding the need and opinion of people regarding diabetes.•Organizations were active in posting tweets, but they didn't take full advantage of communicating features in social media.</abstract><cop>Netherlands</cop><pub>Elsevier Ltd</pub><pmid>34920205</pmid><doi>10.1016/j.dsx.2021.102359</doi><tpages>1</tpages></addata></record> |
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language | eng |
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source | MEDLINE; Elsevier ScienceDirect Journals |
subjects | Content analysis Diabetes Diabetes Mellitus - diagnosis Diabetes Mellitus - epidemiology Health Communication Humans India - epidemiology Public Health Reachability evaluation Social Media |
title | Social media analytics and reachability evaluation - #Diabetes |
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