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  1. Article ; Online: Dataset on dynamics of Coronavirus on Twitter.

    Aguilar-Gallegos, Norman / Romero-García, Leticia Elizabeth / Martínez-González, Enrique Genaro / García-Sánchez, Edgar Iván / Aguilar-Ávila, Jorge

    Data in brief

    2020  Volume 30, Page(s) 105684

    Abstract: ... the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately ... In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health ... types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis ...

    Abstract In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health global crisis. The data were collected through the Twitter REST API search. We used the rtweet R package to download raw data. The term searched was "Coronavirus" which included the word itself and its hashtag version. We collected the data over 23 days, from January 21 to February 12, 2020. The dataset is multilingual, prevailing English, Spanish, and Portuguese. We include a new variable created from other four variables; it is called "type" of tweets, which is useful for showing the diversity of tweets and the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately. On the other hand, they can be crossed to set other researches, among them, trends and relevance of different topics, types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis, as well as to perform social network analysis. This dataset can attract the attention of researchers related to different fields on knowledge, such as data science, social science, network science, health informatics, tourism, infodemiology, and others.
    Keywords covid19
    Language English
    Publishing date 2020-05-08
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2786545-9
    ISSN 2352-3409 ; 2352-3409
    ISSN (online) 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2020.105684
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Dataset on dynamics of Coronavirus on Twitter

    Aguilar-Gallegos, Norman / Romero-García, Leticia Elizabeth / Martínez-González, Enrique Genaro / García-Sánchez, Edgar Iván / Aguilar-Ávila, Jorge

    Data in Brief. 2020 June, v. 30

    2020  

    Abstract: ... the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately ... In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health ... types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis ...

    Abstract In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health global crisis. The data were collected through the Twitter REST API search. We used the rtweet R package to download raw data. The term searched was “Coronavirus” which included the word itself and its hashtag version. We collected the data over 23 days, from January 21 to February 12, 2020. The dataset is multilingual, prevailing English, Spanish, and Portuguese. We include a new variable created from other four variables; it is called “type” of tweets, which is useful for showing the diversity of tweets and the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately. On the other hand, they can be crossed to set other researches, among them, trends and relevance of different topics, types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis, as well as to perform social network analysis. This dataset can attract the attention of researchers related to different fields on knowledge, such as data science, social science, network science, health informatics, tourism, infodemiology, and others.
    Keywords Orthocoronavirinae ; data collection ; social networks ; tourism
    Language English
    Dates of publication 2020-06
    Publishing place Elsevier Inc.
    Document type Article
    ZDB-ID 2786545-9
    ISSN 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2020.105684
    Database NAL-Catalogue (AGRICOLA)

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  3. Article: Dataset on dynamics of Coronavirus on Twitter

    Aguilar-Gallegos, Norman / Romero-García, Leticia Elizabeth / Martínez-González, Enrique Genaro / García-Sánchez, Edgar Iván / Aguilar-Ávila, Jorge

    Data Brief

    Abstract: ... the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately ... In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health ... types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis ...

    Abstract In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health global crisis. The data were collected through the Twitter REST API search. We used the rtweet R package to download raw data. The term searched was "Coronavirus" which included the word itself and its hashtag version. We collected the data over 23 days, from January 21 to February 12, 2020. The dataset is multilingual, prevailing English, Spanish, and Portuguese. We include a new variable created from other four variables; it is called "type" of tweets, which is useful for showing the diversity of tweets and the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately. On the other hand, they can be crossed to set other researches, among them, trends and relevance of different topics, types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis, as well as to perform social network analysis. This dataset can attract the attention of researchers related to different fields on knowledge, such as data science, social science, network science, health informatics, tourism, infodemiology, and others.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #209995
    Database COVID19

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  4. Article ; Online: Dataset on dynamics of Coronavirus on Twitter

    Norman Aguilar-Gallegos / Leticia Elizabeth Romero-García / Enrique Genaro Martínez-González / Edgar Iván García-Sánchez / Jorge Aguilar-Ávila

    Data in Brief, Vol 30, Iss , Pp 105684- (2020)

    2020  

    Abstract: ... the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately ... In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health ... types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis ...

    Abstract In this data article, we provide a dataset of 8,982,694 Twitter posts around the coronavirus health global crisis. The data were collected through the Twitter REST API search. We used the rtweet R package to download raw data. The term searched was “Coronavirus” which included the word itself and its hashtag version. We collected the data over 23 days, from January 21 to February 12, 2020. The dataset is multilingual, prevailing English, Spanish, and Portuguese. We include a new variable created from other four variables; it is called “type” of tweets, which is useful for showing the diversity of tweets and the dynamics of users on Twitter. The dataset comprises seven databases which can be analysed separately. On the other hand, they can be crossed to set other researches, among them, trends and relevance of different topics, types of tweets, the embeddedness of users and their profiles, the retweets dynamics, hashtag analysis, as well as to perform social network analysis. This dataset can attract the attention of researchers related to different fields on knowledge, such as data science, social science, network science, health informatics, tourism, infodemiology, and others.
    Keywords COVID-19 ; Pandemic ; Infodemiology ; Social media ; Twitter ; Retweets ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Science (General) ; Q1-390 ; covid19
    Language English
    Publishing date 2020-06-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  5. Article: COVID-19: The First Public Coronavirus Twitter Dataset

    Chen, Emily / Lerman, Kristina / Ferrara, Emilio

    Abstract: ... coronavirus (COVID-19) Twitter dataset that we have been continuously collecting since January 22, 2020 ... TweetIDs). It is our hope that our contribution will enable the study of online conversation dynamics ... At the time of this writing, the novel coronavirus (COVID-19) pandemic outbreak has already put ...

    Abstract At the time of this writing, the novel coronavirus (COVID-19) pandemic outbreak has already put tremendous strain on many countries' citizens, resources and economies around the world. Social distancing measures, travel bans, self-quarantines, and business closures are changing the very fabric of societies worldwide. With people forced out of public spaces, much conversation about these phenomena now occurs online, e.g., on social media platforms like Twitter. In this paper, we describe a multilingual coronavirus (COVID-19) Twitter dataset that we have been continuously collecting since January 22, 2020. We are making our dataset available to the research community (https://github.com/echen102/COVID-19-TweetIDs). It is our hope that our contribution will enable the study of online conversation dynamics in the context of a planetary-scale epidemic outbreak of unprecedented proportions and implications. This dataset could also help track scientific coronavirus misinformation and unverified rumors, or enable the understanding of fear and panic --- and undoubtedly more. Ultimately, this dataset may contribute towards enabling informed solutions and prescribing targeted policy interventions to fight this global crisis.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  6. Article: The First French COVID19 Confinement Twitter Dataset

    Balech, Sophie / Benavent, Christophe / Calciu, Mihai

    Abstract: In this paper, we present a mainly French coronavirus Twitter dataset that we have been ... conversation dynamics reflecting people sentiments when facing severe home confinement restrictions determined ... We offer our datasets and sentiment analysis annotations, that have been obtained using high performance ...

    Abstract In this paper, we present a mainly French coronavirus Twitter dataset that we have been continuously collecting since confinement restrictions have been enacted in France (in March 17, 2020). We offer our datasets and sentiment analysis annotations, that have been obtained using high performance computing (HPC) capabilities of our university's datacenter, to the research community at https://github.com/calciu/C0VID19-ContainmentFr. We think that our contribution can facilitate analysis of online conversation dynamics reflecting people sentiments when facing severe home confinement restrictions determined by the outbreak of this world wide epidemic. We hope that our contribution will help decode shared experience and mood but also test the sensitivity of sentiment measurement instruments and incite the development of new instruments, methods and approaches.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  7. Book ; Online: The First French COVID19 Lockdown Twitter Dataset

    Balech, Sophie / Benavent, Christophe / Calciu, Mihai

    2020  

    Abstract: In this paper, we present a mainly French coronavirus Twitter dataset that we have been ... datacenter. We think that our contribution can facilitate analysis of online conversation dynamics reflecting ... our datasets and sentiment analysis annotations to the research community at https://github.com/calciu/COVID19 ...

    Abstract In this paper, we present a mainly French coronavirus Twitter dataset that we have been continuously collecting since lockdown restrictions have been enacted in France (in March 17, 2020). We offer our datasets and sentiment analysis annotations to the research community at https://github.com/calciu/COVID19-LockdownFr. They have been obtained using high performance computing (HPC) capabilities of our university's datacenter. We think that our contribution can facilitate analysis of online conversation dynamics reflecting people sentiments when facing severe home confinement restrictions determined by the outbreak of this world wide epidemic. We hope that our contribution will help decode shared experience and mood but also test the sensitivity of sentiment measurement instruments and incite the development of new instruments, methods and approaches.

    Comment: 6 pages, 1 figure, 4 tables
    Keywords Computer Science - Social and Information Networks ; J.4 ; covid19
    Publishing date 2020-05-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: A dataset of media realeases (Twitter, News and Comments, Youtube, Facebook) form Poland related to COVID-19 for open research

    Andrzej Jarynowski

    2020  

    Abstract: ... dynamics during pandemics. With this dataset, we aim to understand mechanisms of COVID-19 epidemic-related ... Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19 ... org tool in language Polish and topic "Coronavirus" in article body; - extracted 1,015,199 (tweets ...

    Abstract Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19), challenging public health mitigation strategies and possibly the political consensus. The widespread use of the traditional and social media on the Internet provides us with an invaluable source of information on societal dynamics during pandemics. With this dataset, we aim to understand mechanisms of COVID-19 epidemic-related social behavior in Poland deploying methods of computational social science and digital epidemiology. We have collected and analyzed COVID-19 perception on the Polish language Internet during 15.01-31.07(06.08) and labeled data quantitatively (Twitter, Youtube, Articles) and qualitatively (Facebook, Articles and Comments of Article) in the Internet by infomediological approach. - manually labeled1,449 articles / Facebook posts from Lower Silesia (facebook_articles_lower_silesia.zip) and 111 texts from outside this region; -extracted 57,306 representative articles (articles_till_06_08.zip) in Polish using Eventregitry.org tool in language Polish and topic "Coronavirus" in article body; - extracted 1,015,199 (tweets_till_31_07_users.zip and tweets_till_31_07_text.zip) and Tweets from #Koronawirus in language Polish usiing Twitter API. - collected 1,574 videos (youtube_comments_till_31_07.zip and youtube_movie.csv) with keyword: Koronawirus on YouTube and 247,575 comments on them using Google API; - We supplemented the media observations with an analysis of 244 social empirical studies till 25.05 on COVID-19 in Poland (empirical_social_studies.csv). Reports and analyzes and coding books can be found in Polish at: http://www.infodemia-koronawirusa.pl
    Keywords covid-19 ; media analysis ; risk perception ; covid19
    Subject code 070
    Language Polish
    Publishing date 2020-08-14
    Publishing country eu
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  9. Book ; Online: A dataset of media realeases (Twitter, News and Comments, Youtube, Facebook) form Poland related to COVID-19 for open research

    Andrzej Jarynowski

    2020  

    Abstract: ... dynamics during pandemics. IWith this dataset we aim to understand mechanisms of COVID-19 epidemic-related ... Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19 ... in language Polish and topic "Coronavirus" in article body; - extracted 1,015,199 (tweets_till_31_07_users.zip ...

    Abstract Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19), challenging public health mitigation strategies and possibly the political consensus. The widespread use of the traditional and social media on the Internet provides us with an invaluable source of information on societal dynamics during pandemics. IWith this dataset we aim to understand mechanisms of COVID-19 epidemic-related social behavior in Poland deploying methods of computational social science and digital epidemiology. We have collected and analyzed COVID-19 perception on the Polish language Internet during 15.01-31.07 and labeled data quantitatively (Twitter, Youtube, Articles) and qualitatively (Facebook, Articles and Comments of Article) in the Internet by infomediological approach. - manually coded 1,449 articles / Facebook posts from Lower Silesia (facebook_articles_lower_silesia.zip) and 111 texts from outside this region; -extracted 57,306 representative articles (articles_till_06_08.zip) in Polish using Eventregitry.org tool in language Polish and topic "Coronavirus" in article body; - extracted 1,015,199 (tweets_till_31_07_users.zip and tweets_till_31_07_text.zip) and Tweets from #Koronawirus in language Polish in Twitter. - collected 1,574 videos (youtube_comments_till_31_07.zip and youtube_movie.csv) with keyword: Koronawirus on YouTube and 247,575 comments on them; - We supplemented the media observations with an analysis of 244 social empirical studies on COVID-19 in Poland (empirical_studies.csv). Reports and analyzes and coding books can be found in Polish at: http://www.infodemia-koronawirusa.pl
    Keywords covid-19 ; media analysis ; risk perception ; covid19
    Subject code 070
    Language Polish
    Publishing date 2020-08-14
    Publishing country eu
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

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  10. Book ; Online: SpanishTweetsCOVID-19

    Tommasel, A (via Mendeley Data)

    A Social Media Enriched Covid-19 Twitter Spanish Dataset

    2020  

    Abstract: This dataset presents a large-scale collection of millions of Twitter posts related ... users and content-based user relations, allowing the observation of the dynamics of the shared ... the adoption of guidelines, the emergence, dynamics and propagation of disinformation and rumours ...

    Abstract This dataset presents a large-scale collection of millions of Twitter posts related to the coronavirus pandemic in Spanish language. The collection was built by monitoring public posts written in Spanish containing a diverse set of hashtags related to the COVID-19, as well as tweets shared by the official Argentinian government offices, such as ministries and secretaries at different levels. Data was collected between March and August 2020 using the Twitter API, and will be periodically updated. In addition to tweets IDs, the dataset includes information about mentions, retweets, media, URLs, hashtags, replies, users and content-based user relations, allowing the observation of the dynamics of the shared information. Data is presented in different tables that can be analysed separately or combined. The dataset aims at serving as source for studying several coronavirus effects in people through social media, including the impact of public policies, the perception of risk and related disease consequences, the adoption of guidelines, the emergence, dynamics and propagation of disinformation and rumours, the formation of communities and other social phenomena, the evolution of health related indicators (such as fear, stress, sleep disorders, or children behaviour changes), among other possibilities. In this sense, the dataset can be useful for multi-disciplinary researchers related to the different fields of data science, social network analysis, social computing, medical informatics, social sciences, among others.
    Keywords Interdisciplinary sciences ; covid19
    Publishing date 2020-11-04T17:48:42.173Z
    Publishing country nl
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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