Social media and the Covid-19 pandemic: Observations from Nigeria

Obi-Ani, Ngozika Anthonia; Anikwenze, Chinenye; Isiani, Mathias Chukwudi

doi:10.1080/23311983.2020.1799483

Cited by 88 publications

(68 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The observations from the Nigerian study of the social media impact of COVID-19 pandemic reported platforms like Twitter, Facebook, and YouTube, which cannot be overemphasized with a plan of action for data dispersal. It indicates that these platforms have been manhandled as individuals cover-up under its secrecy to spread fake news and affect alarm among individuals from the overall population [ 22 ]. In high-population countries like India, it is even worse in spreading fake news online, which could be a potential threat to public health.…”

Section: Introductionmentioning

confidence: 99%

Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models

Chintalapudi

Battineni

Amenta

2021

Infectious Disease Reports

138

View full text Add to dashboard Cite

The novel coronavirus disease (COVID-19) is an ongoing pandemic with large global attention. However, spreading false news on social media sites like Twitter is creating unnecessary anxiety towards this disease. The motto behind this study is to analyses tweets by Indian netizens during the COVID-19 lockdown. The data included tweets collected on the dates between 23 March 2020 and 15 July 2020 and the text has been labelled as fear, sad, anger, and joy. Data analysis was conducted by Bidirectional Encoder Representations from Transformers (BERT) model, which is a new deep-learning model for text analysis and performance and was compared with three other models such as logistic regression (LR), support vector machines (SVM), and long-short term memory (LSTM). Accuracy for every sentiment was separately calculated. The BERT model produced 89% accuracy and the other three models produced 75%, 74.75%, and 65%, respectively. Each sentiment classification has accuracy ranging from 75.88–87.33% with a median accuracy of 79.34%, which is a relatively considerable value in text mining algorithms. Our findings present the high prevalence of keywords and associated terms among Indian tweets during COVID-19. Further, this work clarifies public opinion on pandemics and lead public health authorities for a better society.

show abstract

Section: Introductionmentioning

confidence: 99%

Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models

Chintalapudi

Battineni

Amenta

2021

Infectious Disease Reports

138

View full text Add to dashboard Cite

show abstract

“…However, social media platforms should play a greater role in regulating and fact-checking information distributed on their sites. (Obi-Ani, 2020;Samy et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Disaster Communication Representation on BNPB's Instagram as COVID-19 Response Acceleration Task Force

Nurhajati

Putri

Wijayanto

2021

NJOC

View full text Add to dashboard Cite

Indonesia is one of the countries in Asia that has experienced a severe impact due to the COVID-19 virus. This message was conveyed by the president of Indonesia officially on March 2, 2020. The Indonesian government received various criticisms. The Indonesian people considered the government to be slow in taking a stand on this global pandemic. BNPB (National Disaster Management Agency) was then appointed as the COVID-19 Response Acceleration Task Force. As an agency engaged in disaster issues, BNPB strives to carry out the disaster mitigation process for the COVID-19 case. This study aims to determine how BNPB carries out the representation of disaster communication through Instagram @bnpb_indonesia. The disaster communication process is inseparable from disaster mitigation itself. The concept of successful disaster communication emphasizes the affected, the commitment of the leadership, communication as part of planning and operations in the field, awareness of the situation, and cooperation with the media. This study uses Barthes’s semiotic method to see how denotative, connotative, and mythical forms are formed on BNPB’s Instagram. This preliminary research shows that in general, BNPB Instagram has worked hard to fulfill its organizational profile as a representation of the foremost organization dealing with the COVID-19 disaster in Indonesia. However, in terms of successful communication, several things are not fulfilled on the existing BNPB Instagram display, especially the lack of focus on those affected.Keywords: Representation, disaster communication, covid-19, Instagram, BNPB ABSTRAKIndonesia menjadi salah satu negara di Asia yang mengalami dampak sangat serius akibat virus Covid-19. Hal ini disampaikan presiden Indonesia secara resmi pada tanggal 2 Maret 2020. Berbagai kritik dituai oleh pemerintah Indonesia, masyarakat Indonesia menganggap pemerintah lamban mengambil sikap atas pandemik global ini. BNPB (Badan Nasional Penanggulangan Bencana) kemudian ditunjuk sebagai Gugus Tugas Percepatan Penangangan Covid-19. Sebagai badan yang bergerak pada isu kebencanaan, BNPB berupaya keras melakukan proses mitigasi bencana atas kasus Covid-19. Penelitian ini bertujuan mengetahui bagaimana representasi komunikasi bencana dilakukan BNPB melalui Instagram @bnpb_indonesia. Proses komunikasi bencana tidak terpisahkan dari mitigasi bencana. Konsep keberhasilan komunikasi bencana menekankan fokus pada yang terdampak, adanya komitmen pimpinan, komunikasi sebagai bagian dari perencanaan dan operasi di lapangan, kesadaran atas situasi, serta adanya kerja sama dengan media. Penelitian ini menggunakan metodologi semiotika Barthes untuk melihat bagaimana denotatif, konotatif dan mitos terbentuk atas Instagram BNPB. Penelitian awal ini menunjukkan hasil bahwa secara umum Instagram BNPB berupaya keras memenuhi profil organisasinya sebagai representasi organisasi terdepan yang menangani bencana Covid-19 di Indonesia. Namun dari sisi keberhasilan komunikasinya, ada beberapa hal yang tidak terpenuhi pada tampilan Instagram BNPB yang ada, terutama kurang fokusnya pada yang terdampak.Kata Kunci: Representasi, komunikasi bencana, covid-19, Instagram, BNPB

show abstract

“…The findings of Togun (2020) deviate slightly from that of Obi-Ani et al (2020). For instance, Togun found that though the mass media played a vital role in disseminating information on the Covid -19 pandemic in Nigeria, some of them, especially the social media, propagated fake and inaccurate information about the pandemic.…”

Section: Literature Reviewmentioning

confidence: 96%

Exploring the Relationship Between Exposure to Media Messages on Covid-19 and Compliance with Its Preventive Measures Among Residents of Delta State, Nigeria

Ufuophu-Biri

Bebenimibo

2021

JESR

View full text Add to dashboard Cite

The Covid-19 pandemic that started from Wuhan, China in 2019, has attracted significant scholarly input. Some scholars postulate that the media played a positive and negative role to control and prevent its spread. Nigeria is not left out of this as the pandemic is also prevalent in the country. Therefore, this study examines media coverage of the pandemic in Nigeria and the correlation between the messages and compliance with the pandemic preventive measures. We used the Agenda-Setting theory, which describes how the media brings up specific issues to public discourse and prioritise them above other matters, making the audience perceive some critical topics more than others. We used the survey method and questionnaire to gather the data and used descriptive and inferential statistics to analyse them. We found that the people had frequent exposure to media messages on Covid-19; despite the regular exposure, they complied partially with the Covid-19 preventive measures; there was a significant relationship between exposure to media message on Covid-19 and compliance with its preventive measures. Furthermore, the respondents had a high rating for the media coverage of the pandemic. We recommend that the public sustain the increased exposure of the media messages on Covid-19. Received: 27 February 2021 / Accepted: 6 April 2021 / Published: 10 May 2021

show abstract

Social media and the Covid-19 pandemic: Observations from Nigeria

Cited by 88 publications

References 10 publications

Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models

Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models

Disaster Communication Representation on BNPB's Instagram as COVID-19 Response Acceleration Task Force

Exploring the Relationship Between Exposure to Media Messages on Covid-19 and Compliance with Its Preventive Measures Among Residents of Delta State, Nigeria

Contact Info

Product

Resources

About