Digital inclusion: A mixed-method study of user behavior and content on Twitter.

ABSTRACT:

Objective

This study is the first to explore user behavior and characterize the content shared about digital inclusion on Twitter.

Methods

This mixed-methods research consists of 14,000 tweets featuring the hashtag "#digitalinclusion," posted on Twitter over 15 months. A machine learning technique, latent Dirichlet allocation, was utilized to discover abstract topics within the tweets statistically. The algorithm identified important keywords and text associated with each topic by modeling the underlying word co-occurrence patterns in the dataset. A manual qualitative content analysis was applied to the qualitative data (1000 tweets).

Results

Tweets containing #digitalinclusion are driven by four motives: 1) warning against the risks of digital exclusion; 2) tweets th

SUBMITTER: Salzmann-Erikson M 

PROVIDER: S-EPMC10621295 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature