- [ ] Analyze Content With Word Clouds ### Explanation Idea of clouds (word cloud, hashtag cloud, tweets cloud) is to give a quick overview of the words and concepts dominant in someone’s posts. As it is a time-consuming procedure to read all posts, this technique reduces a time and effort needed to understand the subject’s content. Usually implementations of this approach are not only used for summarizing the posts content, but also calculate the dominance of concepts by calculating the number of times a word appears in collected posts. It further allows filtering the concepts by using the keyword or setting a threshold based on the number of terms. Process: the text of all the suspects’ posts in the given time frame is extracted. A word list is generated for those tweets by counting each letter’s number of times in the tweets. The frequency of appearance is assigned a weight to each word. The word list is presented by the word cloud to increase comprehension. The word with higher weights receives a new visualization. This visualization will show fewer words to obtain a more precise idea of the posts. ### Input - posts ### Output - words list in cloud format (words, corresponding weights) ### Examples - A Multi-Layer Semantic Approach for Digital Forensics Automation for Online Social Networks ### Tools {{some links to tools}} ### Types behavioural ### See also - {{internal links to similar techniques}} ### Weakness [[SOWEL-5. Exposing The Fact Of Activity]]