Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation
Social media is one of the most dominant ways of spreading information. Still, unfortunately, these open platforms provide ways to spreading misinformation which can be extremely dangerous, especially when relevant to sensitive issues such as health-related information. Hence such platforms require...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2023-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/133364 |
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| author | Melanie McCord Fahmida Hamid |
| author_facet | Melanie McCord Fahmida Hamid |
| author_sort | Melanie McCord |
| collection | DOAJ |
| description | Social media is one of the most dominant ways of spreading information. Still, unfortunately, these open platforms provide ways to spreading misinformation which can be extremely dangerous, especially when relevant to sensitive issues such as health-related information. Hence such platforms require an effective autonomous misinformation detection mechanism. Understanding the data is one of the necessary artifacts for building such a mechanism. In this work, we attempted to determine the medical relevancy of cancer-related tweets and explore whether they contain misinformation. We created a dataset of roughly 500 tweets and labeled them according to their medical relevance: medically relevant, not medically relevant, or unrelated to cancer. We ran logistic regression and support vector machine models on them. The highest proportion of correctly identified “medically relevant” tweets, i.e., accuracy, was 0.795. Our analysis hints at some features and factors that can automatically improve cancer-relevant and non-relevant tweet detection. |
| format | Article |
| id | doaj-art-ca50e7cc214e4437aa3b6bc2b3ca39d2 |
| institution | OA Journals |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2023-05-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-ca50e7cc214e4437aa3b6bc2b3ca39d22025-08-20T01:52:22ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622023-05-013610.32473/flairs.36.13336469670Medical Relevancy of Cancer-Related Tweets and Its Relation to MisinformationMelanie McCord0https://orcid.org/0000-0001-6467-3536Fahmida Hamid1https://orcid.org/0000-0002-2344-6297New College of FloridaNew College of FloridaSocial media is one of the most dominant ways of spreading information. Still, unfortunately, these open platforms provide ways to spreading misinformation which can be extremely dangerous, especially when relevant to sensitive issues such as health-related information. Hence such platforms require an effective autonomous misinformation detection mechanism. Understanding the data is one of the necessary artifacts for building such a mechanism. In this work, we attempted to determine the medical relevancy of cancer-related tweets and explore whether they contain misinformation. We created a dataset of roughly 500 tweets and labeled them according to their medical relevance: medically relevant, not medically relevant, or unrelated to cancer. We ran logistic regression and support vector machine models on them. The highest proportion of correctly identified “medically relevant” tweets, i.e., accuracy, was 0.795. Our analysis hints at some features and factors that can automatically improve cancer-relevant and non-relevant tweet detection.https://journals.flvc.org/FLAIRS/article/view/133364 |
| spellingShingle | Melanie McCord Fahmida Hamid Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| title | Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation |
| title_full | Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation |
| title_fullStr | Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation |
| title_full_unstemmed | Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation |
| title_short | Medical Relevancy of Cancer-Related Tweets and Its Relation to Misinformation |
| title_sort | medical relevancy of cancer related tweets and its relation to misinformation |
| url | https://journals.flvc.org/FLAIRS/article/view/133364 |
| work_keys_str_mv | AT melaniemccord medicalrelevancyofcancerrelatedtweetsanditsrelationtomisinformation AT fahmidahamid medicalrelevancyofcancerrelatedtweetsanditsrelationtomisinformation |