We differentiated between computational approaches (either based on volume data, such as the number of mentions related to a party or candidate or the occurrence of particular
hashtags; or endorsement data, such as the number of Twitter followers, Facebook friends or the number of «likes» received on Facebook walls), sentiment analysis approaches, that pay attention to the language and try to attach a qualitative meaning to the comments (
posts, tweets) published by social media users employing automated tools for sentiment analysis (i.e., via natural language processing models or the employment of pre-defined ontological dictionaries), and finally what we call supervised and aggregated sentiment analysis (SASA), that is, techniques that exploit the human codification
in their process and focus on the estimation of the aggregated distribution of the opinions, rather than on individual classification of each
single text (Ceron et al. 2016).
No matter if you are
single, engaged, and / or married you can join
in on the FUN by simply tagging me
in your photo a blog
post, Instagram, Twitter and / or Facebook on how you LOVE THYSELF better be sure to use the
hashtag: #FAITHLOVETHYSELF