We present a thorough characterization of what we believe to be the first analysis of the behavior of groups in WhatsApp in the scientific. Our characterization of over 270,000 messages and about 7,000 users a 28-day period is done at three different layers. The message layer on individual messages, each of which is the result of specific posts by a user. The user layer characterizes the user actions while with a group. The group layer characterizes the aggregate message of all users that participate in a group. We analyze 81 public groups WhatsApp and classify them into two categories, political and non-political according to keywords associated with each group. Our contributions are-fold. First, we introduce a framework and a number of metrics to the behavior of communication groups in mobile messaging systems as WhatsApp. Second, our analysis underscores a Zipf-like profile for user in political groups. Also, our analysis reveals that Whatsapp messages multimedia, with a combination of different forms of content. Multimedia (i.e., audio, image, and video) and emojis are present in 20% and 11.2% all messages respectively. Political groups use more text messages than-political groups. Second, we characterize novel features that represent the of a public group, with multiple conversational turns between key, with the participation of other members of the group.
No takes yet. Share an insight, caveat, or question.
Caetano et al. (2018) studied this question.