COVID‐19 pandemic and African innovation: Finding the good from the bad using Twitter data and text mining approach-Reference-Cited by-同舟云学术

COVID‐19 pandemic and African innovation: Finding the good from the bad using Twitter data and text mining approach

Published:2022-11-30 Issue: Volume: Page:
ISSN:0020-8701
Container-title:International Social Science Journal
language:en
Short-container-title:Int Social Sci J

Author:

Asare Andy Ohemeng¹^ORCID,Sarpong Eric Ohemeng²,Truong holds Ngoc³,Osei‐Bonsu Patrick⁴,Ahado Samuel⁴,Mensah William Gyasi⁴

Affiliation:

1. Professor George Brown College 200 King Street East Toronto Ontario Canada

2. University of Electronics Science and Technology of China No.2006, Xiyuan Avenue. West Hi‐Tech. Zone Chengdu P.R. China

3. George Brown College 200 King Street East Toronto Ontario Canada

4. University of Electronic Science and Technology of China No.2006, Xiyuan Avenue West Hi‐Tech. Zone Chengdu P.R. China

Publisher

Wiley

Subject

General Social Sciences

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/issj.12386

Reference68 articles.

1. Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

2. Adu P.2020a. Conducting Qualitative Analysis of Social Media (Twitter) Data Using NVivo 11.

3. Adu P.2020b. ‘Understanding the Applications Strengths and Limitations of Automatic Qualitative Coding’ (January). doi:10.13140/RG.2.2.14156.16002.

4. Angelelli P.et al.2020. ‘Responding to COVID‐19 with Science Innovation and Productive Development’ p. 51.

5. Arone2020. Revolutionizing Delivery in Africa! Available at:https://aronedelivery.com/.

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