The biggest advantage of Voyant in my work is to get an overall sense of a corpus of texts—to discover interesting facets of texts or patterns that occur through texts. It is possible to track the use of a particular term or related terms through a single text or through multiple texts and visualize these results so that frequency, placement and some sense of context for these the presence for particular words or phrases. Using Voyant in this way might initiate a wider understanding of relationships among texts; one can see differences or similarities among texts from different authors, time periods, geographical locations, etc. Voyant may be used as a preliminary assessment of a set of texts to inform a larger research project. I am interested in how Voyant might be used for non-literary texts. News articles, blog posts, databases or journal articles could be tracked for instances, frequency and placement of certain words or phrases.
Voyant is extremely user-friendly and the visualizations users create are easily exportable. One can use Voyant without creating a login or downloading anything. Considering its affordances for particular types of work, limitations, however few, should be acknowledged. The most striking limitation is that texts must be uploaded to Voyant. Therefore the text must be in a digital format in which words are 'recognized.' And, the more you try to do with the tool, the messier input, visualization and analysis becomes.
The visualizations one can make with Voyant are great for starting conversations, they can facilitate analysis and observation, and can be used to clearly communicate complex relationships between texts or words. I would recommend this tool most highly for any preliminary scholarly investigation, as well as for pedagogical purposes focusing on interpreting, understanding and producing literary work.
To use Voyant, navigate to its website and past in links, pdfs or other types of text directly into the tool. One can find a number of examples vetted by Voyant's developers in Voyant's documentation gallery. One I found particularly exemplary of the advantages and optimal use of Voyant for starting conversations about themes, word usage, topics and relations between these in texts is Mark Sample's, no life, 1,000,000,000,000,000 stanzas of House of Leaves of Grass.
The “Topic Modelling Tool” (TMT), available through the Google Code Repository, provides quick and easy topic model generation and navigation. The TMT is easy to install. With a working Java application on any platform, download the TMT program and click on it to run it. Java will open the program.
The advantages of the TMT are its availability and use. Using these tutorials from Graham, Shawn, Ian Milligan, Scott Weingart, it is easy to perform topic modelling, or to text analysis of a large corpuses of textual information. It is an attempt to inject semantic meaning into vocabulary. Topics are collections of words co-occurring in documents across a corpus. You can name topics, and/or assign meaning to them to see how topics are arranged in the corpus. Because topic modeling creates models, researchers should consider the entire model as they analyze their results. Herein lies the main limitation of the tool for digital humanities work. Focusing too much on a single topic without considering the others may invalidate the results. Before you begin with topic modeling, you should seriously consider your research question and whether this type of distant reading is useful to your project. Matthew Kirschenbaum’s Distant Reading is a good place to start if one is interested in understanding when this type of work is warranted and when it is not.
A great example of the use of the TMT for scholarly research can be found in Cameron Blevins' Topic Modeling Martha Ballard's Diary. One can see how Blevins has highlighted topics found in the texts of the diaries and visualized and analyzed these findings, while maintaining a critical awareness of the limitations of the TMT as a research resource.
In the days before I used Zotero, I allotted at least an entire day of paper editing to add and perfect the footnotes and references. Zotero's greatest advantage is that it streamlines this process—one can insert already perfectly-formatted footnotes and references on the fly with the help of the Zotero Firefox browser and word processor plug-ins. This vastly simplifies and expedites collaborative work that draws from a number of sources. The "network effects" of Zotero had been a negative aspect of the application for collaborative work in the past—very few people worked with it and developed it, and thus it was buggier and harder to use with groups—but over the last few years this has changed. It is now the most popular and developed application for citation work "on the market". The fact that it is a "free and open source" application, means that it is free to use and relies on no API, so it will never be shut down when a corporate application to which the API manages access updates or shuts down. The open source nature of the application also allow a number of related developed plug-ins and add-ons to do about anything anyone envisions. For example, there are a number of additional plug-ins that allow for easy citation analyses. The application also has the ability to synchronize across devices, provided that they are desktop/laptop devices, with a single sign in username and password. This further facilitates the ease of use and collaborative nature of the applicaiton.
The drawbacks of Zotero are that while the project is open source, a number of the plug-ins can be buggy. It does not work with any browser but Firefox, which is itself increasingly buggy. It does not work with mobile and tablet devices.
To get started with Zotero, navigate to https://www.zotero.org/ in a Firefox browser and follow the prompts. Be sure that your word processing application is not open and running when you do this so that the plug in successfully updates to your word processor when you open it next. There are many tutorials online to get you on the way to successfully using Zotero. I suggest this tutorial by UCLA library.