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Data · dataset · 2018

TopicBased

Listed in Teesside University Research Data Repository

In this work, we present a dataset, which is collected from English-language Wikipedia and Twitter users.

Description

In contrast to the corpus of existing studies, we focused on the corpus of Wikipedia, which contains many articles and covers a multitude of topics. We performed preprocessing, including lemmatizing, converting slang into common English, and removing stop words.

Then the articles in the English-language version of Wikipedia were converted to plain text. The Wiki markup was processed and a text version of each item was returned. By using Tweepy [1] to access the Twitter API, we collected the data from Twitter users.

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We crawled the list of each user account’s followers. Next, we obtained the most recent tweets of each user in the study.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Text 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/7hwv9r35np.119 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:social-sciencemapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:textenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title