*An informal institution comparative study of occupational safety knowledge 
sharing via French and English Tweets: languaculture, weak-strong ties and AI 
sentiment perspectives*
Abstract
To study the social structure of English and French Tweets of occupational 
safety and their sentiment distributions, this study applied NodeXL and 
MeaningCloud to analyse 17,147 English Tweets and 16,618 French Tweets about 
“occupational safety” in Twitter. We found that French and English Twitter 
users who are interested in this topic did not usually interact. While top 
English Twitter influencers were professors, top French influencers were 
government officers and individuals. Clusters of Twitter members interested in 
occupational safety had a low tendency to reach people in other groups. Most 
failed to make good use of weak ties to increase their impact and shared 
information about occupational safety outside their circle of friends. This 
overthrows previous research that Twitter’s social network was built based on 
the weak tie: Twitter users follow commentators, celebrities, and opinion 
leaders who do not know personally. Besides, we also conducted sentiment 
analysis via machine learning algorithms. We found that the more positive 
sentiment of an English Tweets, the more likely it will be retweeted. Yet, the 
more negative sentiment of a French Tweets, the more likely the Tweets will be 
retweeted. Thus, negative occupational safety Tweets have stronger impacts than 
positive ones among French but not English Tweets. While sentiment analysis 
results of French Tweets indicated that most Twitter users discussed 
occupational safety issues with a neutral tone, the number of extreme negative 
in French Tweets was a lot more than that of English. That reflects 
languaculture differences, and informal institutions impact users’ behaviours.


An informal institution comparative study of occupational safety knowledge 
sharing via French and English Tweets: languaculture, weak-strong ties and AI 
sentiment perspectives - ScienceDirect 
<https://www.sciencedirect.com/science/article/pii/S0925753521004422?dgcid=coauthor>
------------------------------------------
Artificial General Intelligence List: AGI
Permalink: 
https://agi.topicbox.com/groups/agi/Tbcc462846d104821-M2d37bb6566794333222d646b
Delivery options: https://agi.topicbox.com/groups/agi/subscription

Reply via email to