In this Week, we have learnt about how to analyze a text and count the frequency of words using different tools (http://www.wordle.net) (http://many-eyes.com) and (http://voyant-tools.org) to surf and stumble with the text. In These electronic web sites, we can upload a set of data or information to see which words are most often used and which are used the least in which this information will be analyzed and then displayed in different ways such as maps and charts. I have applied these three tools on the data created previously from Archive Twitter and Almetrics analysis.
This website requires sign in to use its features. I have created my account and upload the data created from Twitter and Almetrics analysis, however, the website was very slow and the page took long times to response. This web site has a variety of visualizations can be selected from its collection, and allow some customisation such font and the legend mode. Although this web site is very slow, it allows users to remove some unmeaning words as shown below. In addition, when the size of data uploaded is small, Many Eyes response is quickly and the opposite is true.
Voyant is the best tools and it is still under continuing development by its creators. This website performs advanced level of text analysis comparing to the previous methods as it analyses the text in seconds and removes the unwanted words in order to produce a meaning word cloud as shown below. However, Voyant is unable to modify some common features such as font and colours.
Voyant tools goes beyond the word cloud and provides users with more information about the text including a full text reader, summary, a word trends graph, the frequency and the count of words in the entire corpus, and to exclude individual words and see how they appears in the documents and the context. The screenshots below demonstrate the data created from Twitter and Almetrics analysis. for Example, from the screenshot of data created by Almetrics, as we can see the most frequent words were disaster and health. On the other hand, from the data created by Twitter Analysis, the most used word in the entire corpus was the hashtag cyclist. We can also exclude any word and see more information about it. For example, we highlighted the word Analysis to obtain more information how it appears in document and context.
Word cloud may be a good method to know the most important keywords of the text and to obtain quantitative analysis. However, it is not a good qualitative method. Another tools such as Voyant can tell more about the text and provide users with more information about the text, but, more development in these tools is required to obtain advanced quantitative and qualitative analysis.