Social Media Mining Toolkit (SMMT)
There has been a dramatic increase in the popularity of utilizing social media data for research purposes within the biomedical community. In PubMed alone, there have been nearly 2,500 publication entries since 2014 that deal with analyzing social media data from Twitter and Reddit. However, the vas...
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| Format: | Article |
| Language: | English |
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BioMed Central
2020-06-01
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| Series: | Genomics & Informatics |
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| Online Access: | http://genominfo.org/upload/pdf/gi-2020-18-2-e16.pdf |
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| _version_ | 1832574137102499840 |
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| author | Ramya Tekumalla Juan M. Banda |
| author_facet | Ramya Tekumalla Juan M. Banda |
| author_sort | Ramya Tekumalla |
| collection | DOAJ |
| description | There has been a dramatic increase in the popularity of utilizing social media data for research purposes within the biomedical community. In PubMed alone, there have been nearly 2,500 publication entries since 2014 that deal with analyzing social media data from Twitter and Reddit. However, the vast majority of those works do not share their code or data for replicating their studies. With minimal exceptions, the few that do, place the burden on the researcher to figure out how to fetch the data, how to best format their data, and how to create automatic and manual annotations on the acquired data. In order to address this pressing issue, we introduce the Social Media Mining Toolkit (SMMT), a suite of tools aimed to encapsulate the cumbersome details of acquiring, preprocessing, annotating and standardizing social media data. The purpose of our toolkit is for researchers to focus on answering research questions, and not the technical aspects of using social media data. By using a standard toolkit, researchers will be able to acquire, use, and release data in a consistent way that is transparent for everybody using the toolkit, hence, simplifying research reproducibility and accessibility in the social media domain. |
| format | Article |
| id | doaj-art-ee8c837214fe4657afa3997fb9f92f26 |
| institution | Kabale University |
| issn | 2234-0742 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | BioMed Central |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj-art-ee8c837214fe4657afa3997fb9f92f262025-02-02T01:06:02ZengBioMed CentralGenomics & Informatics2234-07422020-06-01182e1610.5808/GI.2020.18.2.e16605Social Media Mining Toolkit (SMMT)Ramya TekumallaJuan M. BandaThere has been a dramatic increase in the popularity of utilizing social media data for research purposes within the biomedical community. In PubMed alone, there have been nearly 2,500 publication entries since 2014 that deal with analyzing social media data from Twitter and Reddit. However, the vast majority of those works do not share their code or data for replicating their studies. With minimal exceptions, the few that do, place the burden on the researcher to figure out how to fetch the data, how to best format their data, and how to create automatic and manual annotations on the acquired data. In order to address this pressing issue, we introduce the Social Media Mining Toolkit (SMMT), a suite of tools aimed to encapsulate the cumbersome details of acquiring, preprocessing, annotating and standardizing social media data. The purpose of our toolkit is for researchers to focus on answering research questions, and not the technical aspects of using social media data. By using a standard toolkit, researchers will be able to acquire, use, and release data in a consistent way that is transparent for everybody using the toolkit, hence, simplifying research reproducibility and accessibility in the social media domain.http://genominfo.org/upload/pdf/gi-2020-18-2-e16.pdfdata mininginformation storage and retrievalmachine learningsocial media |
| spellingShingle | Ramya Tekumalla Juan M. Banda Social Media Mining Toolkit (SMMT) Genomics & Informatics data mining information storage and retrieval machine learning social media |
| title | Social Media Mining Toolkit (SMMT) |
| title_full | Social Media Mining Toolkit (SMMT) |
| title_fullStr | Social Media Mining Toolkit (SMMT) |
| title_full_unstemmed | Social Media Mining Toolkit (SMMT) |
| title_short | Social Media Mining Toolkit (SMMT) |
| title_sort | social media mining toolkit smmt |
| topic | data mining information storage and retrieval machine learning social media |
| url | http://genominfo.org/upload/pdf/gi-2020-18-2-e16.pdf |
| work_keys_str_mv | AT ramyatekumalla socialmediaminingtoolkitsmmt AT juanmbanda socialmediaminingtoolkitsmmt |