Examples of tweets texts (Portuguese).
<div><p>The main objective of this study is to describe the process of collecting data extracted from Twitter (X) during the Brazilian presidential elections in 2022, encompassing the post-election period and the event of the attack on the buildings of the executive, legislative, and jud...
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2025
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| _version_ | 1852023070404902912 |
|---|---|
| author | Sylvia Iasulaitis (8301189) |
| author2 | Alan Demétrius Baria Valejo (20660639) Bruno Cardoso Greco (20660642) Vinicius Gonçalves Perillo (20660645) Guilherme Henrique Messias (20660648) Isabella Vicari (20660651) |
| author2_role | author author author author author |
| author_facet | Sylvia Iasulaitis (8301189) Alan Demétrius Baria Valejo (20660639) Bruno Cardoso Greco (20660642) Vinicius Gonçalves Perillo (20660645) Guilherme Henrique Messias (20660648) Isabella Vicari (20660651) |
| author_role | author |
| dc.creator.none.fl_str_mv | Sylvia Iasulaitis (8301189) Alan Demétrius Baria Valejo (20660639) Bruno Cardoso Greco (20660642) Vinicius Gonçalves Perillo (20660645) Guilherme Henrique Messias (20660648) Isabella Vicari (20660651) |
| dc.date.none.fl_str_mv | 2025-02-03T18:27:55Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0316626.t007 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Examples_of_tweets_texts_Portuguese_/28336004 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified three major stages primary collection type extracting valuable information brazilian presidential elections available api keys public &# 8221 data collection strategy big social data big data standards named &# 8220 brazil </ p 282 million tweets 2022 presidential elections collecting data extracted &# 8220 xlink "> trivial due sociopolitical areas several processes python algorithms preliminary analysis political purposes main objective judiciary branches january 2023 interdisciplinary nature informational studies extensive dataset election period dataset created contextual analysis br ), |
| dc.title.none.fl_str_mv | Examples of tweets texts (Portuguese). |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <div><p>The main objective of this study is to describe the process of collecting data extracted from Twitter (X) during the Brazilian presidential elections in 2022, encompassing the post-election period and the event of the attack on the buildings of the executive, legislative, and judiciary branches in January 2023. The work of collecting data took one year. Additionally, the study provides an overview of the general characteristics of the dataset created from 282 million tweets, named “The Interfaces Twitter Elections Dataset” (ITED-Br), the third most extensive dataset of tweets with political purposes. The process of collecting and creating the database for this study went through three major stages, subdivided into several processes: (1) A preliminary analysis of the platform and its operation; (2) Contextual analysis, creation of the conceptual model, and definition of Keywords and (3) Implementation of the Data Collection Strategy. Python algorithms were developed to model each primary collection type. The “token farm” algorithm, was employed to iterate over available API keys. While Twitter is generally a “public” access platform and fits into big data standards, extracting valuable information is not trivial due to the volume, speed, and heterogeneity of data. This study concludes that acquiring informational value requires expertise not only in sociopolitical areas but also in computational and informational studies, highlighting the interdisciplinary nature of such research.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_6fe1d8d81453da4f37e358a36d2f1e44 |
| identifier_str_mv | 10.1371/journal.pone.0316626.t007 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28336004 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Examples of tweets texts (Portuguese).Sylvia Iasulaitis (8301189)Alan Demétrius Baria Valejo (20660639)Bruno Cardoso Greco (20660642)Vinicius Gonçalves Perillo (20660645)Guilherme Henrique Messias (20660648)Isabella Vicari (20660651)BiotechnologyScience PolicyBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedthree major stagesprimary collection typeextracting valuable informationbrazilian presidential electionsavailable api keyspublic &# 8221data collection strategybig social databig data standardsnamed &# 8220brazil </ p282 million tweets2022 presidential electionscollecting data extracted&# 8220xlink ">trivial duesociopolitical areasseveral processespython algorithmspreliminary analysispolitical purposesmain objectivejudiciary branchesjanuary 2023interdisciplinary natureinformational studiesextensive datasetelection perioddataset createdcontextual analysisbr ),<div><p>The main objective of this study is to describe the process of collecting data extracted from Twitter (X) during the Brazilian presidential elections in 2022, encompassing the post-election period and the event of the attack on the buildings of the executive, legislative, and judiciary branches in January 2023. The work of collecting data took one year. Additionally, the study provides an overview of the general characteristics of the dataset created from 282 million tweets, named “The Interfaces Twitter Elections Dataset” (ITED-Br), the third most extensive dataset of tweets with political purposes. The process of collecting and creating the database for this study went through three major stages, subdivided into several processes: (1) A preliminary analysis of the platform and its operation; (2) Contextual analysis, creation of the conceptual model, and definition of Keywords and (3) Implementation of the Data Collection Strategy. Python algorithms were developed to model each primary collection type. The “token farm” algorithm, was employed to iterate over available API keys. While Twitter is generally a “public” access platform and fits into big data standards, extracting valuable information is not trivial due to the volume, speed, and heterogeneity of data. This study concludes that acquiring informational value requires expertise not only in sociopolitical areas but also in computational and informational studies, highlighting the interdisciplinary nature of such research.</p></div>2025-02-03T18:27:55ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0316626.t007https://figshare.com/articles/dataset/Examples_of_tweets_texts_Portuguese_/28336004CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/283360042025-02-03T18:27:55Z |
| spellingShingle | Examples of tweets texts (Portuguese). Sylvia Iasulaitis (8301189) Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified three major stages primary collection type extracting valuable information brazilian presidential elections available api keys public &# 8221 data collection strategy big social data big data standards named &# 8220 brazil </ p 282 million tweets 2022 presidential elections collecting data extracted &# 8220 xlink "> trivial due sociopolitical areas several processes python algorithms preliminary analysis political purposes main objective judiciary branches january 2023 interdisciplinary nature informational studies extensive dataset election period dataset created contextual analysis br ), |
| status_str | publishedVersion |
| title | Examples of tweets texts (Portuguese). |
| title_full | Examples of tweets texts (Portuguese). |
| title_fullStr | Examples of tweets texts (Portuguese). |
| title_full_unstemmed | Examples of tweets texts (Portuguese). |
| title_short | Examples of tweets texts (Portuguese). |
| title_sort | Examples of tweets texts (Portuguese). |
| topic | Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified three major stages primary collection type extracting valuable information brazilian presidential elections available api keys public &# 8221 data collection strategy big social data big data standards named &# 8220 brazil </ p 282 million tweets 2022 presidential elections collecting data extracted &# 8220 xlink "> trivial due sociopolitical areas several processes python algorithms preliminary analysis political purposes main objective judiciary branches january 2023 interdisciplinary nature informational studies extensive dataset election period dataset created contextual analysis br ), |