We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamical properties, while properly detrending for the time-dependent features of a signal. Th...

We present a weakly supervised approach for learning hashtags, hashtag patterns, and phrases associated with five emotions: AFFECTION, ANGER/RAGE, FEAR/ANXIETY, JOY, and SADNESS/DISAPPOINTMENT. Starting with seed hashtags to label an initial set of tweets, we train emotion classifiers and use them to learn new emotion hashtags and hashtag patterns. This process then repeats in a bootstrapping f...

The purpose of this study is to determine the types social media platforms used by proponents and opponents vaccination. This research employs a qualitative approach, analyzing hashtag data with Q-DAS (Qualitative Data Analysis Software) Nvivo 12Plus. finds that: First, was spread both sides' narratives content. Second, relation tends be quite strong, but pro-side stronger than contra-side. Thi...

Many events, for instance in sports, political events, and entertainment, happen all over the globe all the time. It is difficult and time consuming to notice all these events, even with the help of different news sites. We use tweets from Twitter to automatically extract information in order to understand hashtags of real-world events. In our paper, we focus on the topic identification of a ha...

Microblogging services, in which users can publish and share personal status, are now very popular, and attracting more and more industrial and scientific interests. Twitter is one of the most famous microblogging services. On twitter, Users can post personal updates, which are called tweets and limited to 140 characters long. In tweets, users can share interesting messages to their friends by ...