510: Digital Humanities

 Chapter seven introduces the idea and significance of quantifying literature through data mining. through quantifying ad data mining we can observe different patterns and analyze data within different texts, articles, books, etc. Different literary resources like Voyant, developed by Geoffrey Rockwell and Stefan Sinclair- which we used in class, allows users to easily distinguish different patterns like different words and how many times throughout the text they were used- along with where in the text you can find said words, recurring phrases, and different themes found in the text. As Quantifying Literature stated, "sometimes the data exposes trends or repetitions that are invisible to a casual reader." With that, identifying and analyzing different patterns and themes allows the reader a fresh, different understanding of literature.  Data mining is the process of analyzing text, video, pictures, and audios and is very important in terms of analyzing different texts. Throu...

  Chapter 7, Data Mining and quantifying literature, explains how analyzing data from texts, images, and auditory files can help point us in a direction of beginning research. Data analysis allows us to pull out patterns of a piece of work that can be recognized as part of the works overall theme, topic, and mood. Text analysis in particular is a “subset of data mining that focuses on the analysis of language” (Underwood 2017). Patterns of terminology, vocabulary, and nomenclature contribute to the textual analysis of language. Furthermore, one can analyze a specific work of text and then compare it to a larger corpus in order to pull out larger themes. Generalizability and reliability “determine the extent to which the results of an analysis can be applied outside the single sample”. Before textual analysis can take place, distant reading but first be put into practice. Distant reading was first introduced in 2000 by Franco Moretti. Distant reading is “the idea of processing conte...

Alex Forbes ENGL 510 Malinda White September 29th      Drucker emphasizes the importance of quantifying literature, and how it can help readers to better understand what they are reading, "the act of quantifying literature, while it may seem reductive, opens up new avenues for understanding texts" (112). Digital tools like Voyant help to reveal patterns and connections that you may not be able to interpret through traditional reading methods. Obtaining quantitative data from literature can be both enlightening as well as controversial. For instance, while tools like Voyant offer a way to visualize and analyze vast amounts of text, allowing us to identify trends and themes that might not be immediately apparent, Voyant also gives us a narrow view of the text, failing to provide context that may be essential to understanding the quantitative data. For instance, through text mining, you can discern the frequency of specific words or phrases thus offering insights into repeat...

  Based on chapter seven about quantifying lectures, analysis and data mining can be an efficient way to identify patterns and give clues in literary texts that might have been missed within close reading.  Using tools like Voyant we are able to take pieces of literature and get a whole new perspective and new artistic creations. Using patterns, recurring words or phrases and thematic tendencies we are able to recognize details that were previously overlooked or deemed insignificant. The ability for websites like Voyants to show both predicted and unexpected patterns is a large benefit and why many find these tools so engaging. As the writer of Quantifying Literature says, “sometimes the data exposes trends or repetitions that are invisible to a casual reader.”. We are often unable to identify the meaning or the subject, frequency analysis can highlight specific themes throughout the author's work. We are able to comprehend and understand to a better degree about the main poi...

     As we are learning, Digital Humanities contains of the various ways that data can be analyzed, quantified and organized by engaging with different materials. This week the use of Voyant Tools with our author texts was a way to expand on information visualization and alter the way that online texts can be understood. Through statistical and computational methods, quantifying literature counts and measures various aspects of text. This is also referred to as Distant Reading, where people are able to study the patterns on a larger scale. Voyant Tools does this with our author texts by measuring the occurrence of certain words or phrases used in texts by different authors. It also provides the lexile diversity, stylistic changes and authorship attributions that contribute to the sentence length and punctuation. Quantifying literature allows people to get a closer look at the significance of patterns over an entire piece of writing.      " One thing he play...

  Blog post 5: Data mining & quantifying literature “Data mining is an automated analysis that looks for patterns and extracts meaningful information in digital files.” This quote is a great example of how you can look at interesting patterns and insights from large datasets, utilizing techniques such as clustering, classification, and predictive analytics using data mining. Voyant is a great example of this concept because it allows users to explore and visualize textual data interactively. With features like word frequency analysis, topic modeling, and sentiment analysis, Voyant enables researchers and analysts to uncover trends and relationships within texts, transforming qualitative data into quantitative insights. This makes it an invaluable resource for anyone looking to leverage data mining techniques to understand complex narratives, identify themes, and gain deeper insights into textual datasets. When using Voyant for our project, I was able to look at complex factors ...

    Quantifying literature can be done incredibly quickly with the help of resources such as Voyant. But what does this information actually tell us? Tools like Voyant help to highlight patterns within a body of text through visualizations like Wordclouds and Bubblelines. I have found these visualizations incredibly helpful especially as a first-time Voyant user. After seeing the most popular words in a text through the Wordcloud, such as in the text I'm analyzing, The Tell-Tale Heart , I can make assumptions about the content of the story, the author's writing style, or what tone/mood that the author is trying to evoke. My Wordcloud  shows the most popular words in the story to be "old", "night", "man", and "heard". From this, I can make assumptions that Poe was going for a darker tone in his writing, and that our story takes place at night time, and that one of the characters is an old man. In my opinion, this source was helpful, but pr...

Chapter 7 discusses data mining and how it is an efficient tool to understanding aspects of literature that would not be possible by just reading it. In my last blog post, I defined data mining as, "the analysis of digital data through searching for patterns that may assist in determining meaning". Quantifying literature offers a new perspective on how works of writing a viewed. Through turning qualitative data into qualitative data, literature is able to be viewed from a more objective lens. From quantifying literature, the researcher is able to view how many words are used, how many times each word is used, where each word is used, or even what words are often connected to other commonly used words throughout the piece of literature. It is up to the researcher to interpret the significance of this data as it might not be very obvious on first glance. Quantifying literature can also help compare two or more different works. This could offer insight a multitude of different a...

  Data mining is a way of finding the patterns in a piece of text or media by having a computer examine the digital file. Based on what I have read this week from the topic’s material, I think that using analytics and computers to extract data from literature and art can have both positives and negatives. T ools available on programs like Voyant can be helpful to know the basics and the measurements of a story. Word count, frequently used terms, their collocations, and their frequency over time in the text can all be interesting to examine. I t is facts that stick out from the mass of words that give us something substantial to say about the story. More advanced computers and analysis, as described in the textbook chapter, can even perhaps determine genre and theme. This ‘distant reading’ of a text gives quantifiable results, but it has its downsides, too. Taking a quote from the textbook that stood out to me, “While patterns emerge , and the large trends can be discerned, the...

     When I first started reading about data mining and distant reading last week I wasn't really sure of what purpose it could have. It seemed to me that this method of interacting with literature or art would leave out important context or subtleties in language. The meaning in literature is created by the careful placement of words and I couldn't really understand what use it would be to reduce all this down into quantitative data to be analyzed by a machine. However, after reading more about it and working with Voyant myself I feel like I am getting a better grasp on the use looking at art in this way can have. Close reading and distant reading are not mutually exclusive. Instead distant reading adds to the interpretive power of close reading by allowing for analysis of a larger body of work. It would be impossible to read every book that was published in a certain decade, but by utilizing distant reading practices a person could identify greater literary patterns and...

  Data visualizations are there to give visual context to raw data. When looking at a series of data stretched over a period, the data can be overwhelming to consume and understand. Just like any graph data visualizations are broken down. This shows how data affects a particular situation over time. Often through an x and y axis. However, data visualizations are not limited to a classical graphical style. There are many styles and ways of analyzing literary works and other media mediums. In simple terms data visualizations are just visual examples that break down copious amounts of data.   Let's compare two concepts (Close Reading and Distant Reading). Close reading stands for microscopic investigation of word choice in literature, whereas distant reading does this through accessing metadata rather than individually recognizing diction.   When relating close   reading to distant reading it's sort of ironic to think about since the term inology sugges...

       Information visualization and distant reading have dramatically reshaped how data interpretation and analysis are approached, particularly in projects such as “Six Degrees of Francis Bacon” and “Yesterday, Today, Tomorrow”. These projects, which rely on network analysis and computational tools, demonstrate the combination of distant reading and data visualization to find patterns and relationships in large amounts of historical and literary data.       “Six Degrees of Francis Bacon” is an excellent example of distant reading since it visualizes the relationships between historical figures in early England, allowing us to see social networks and connections that would be practically impossible to identify through traditional close reading methods. Distant reading as advocated by the literary scholar, Franco Moretti, stresses the importance of large-scale patterns rather than singular events or individuals. The advantages of this strategy are...

     As we are moving on with our learning of Digital Humanities and its vast variety of classification chapter 6 and 7 discuss information visualization and distant reading. Beginning with chapter 6, information visualization is generally speaking a way to show quantified data in a visual manor. Often times these visualizations are forms of graphs, charts or diagrams and assess specific patterns within large amounts of data. One piece from this chapter that I wanted to focus on was how to specifically read these visualizations and understand all of the components. The relationship of data to visualization is to try and find the most reasonable way to portray information and what certain aspects of the visualization are going to best serve the viewers.        Close reading and distant reading are differing terms that relate to analyzing text. Close reading is careful and detailed analysis of a singular text rather distant reading is of large bodie...

    Chapter 6 and 7 along with the additional sources added to my understanding of digital humanities as a whole. The key part of chapter 6 was learning what information visualization was and how it is used. All information visualizations are metrics expressed as graphics. Part of everyday communications and scholarships. The book described it as data that can be difficult to interpret in tabular form. This is useful for seeing patterns within large amounts of information. Anything that can be quantified can be put into information visualizations. Making graphics by hand takes a lot of time. Two portions are metrics and graphics. There are helpful guidelines that can be helpful when deciphering what type of chart should be used. A fun fact is the earliest record of visualization was the observation of the planets and other natural cycles.       Chapter 7 discusses data mining and text analysis. Data mining is the automated analysis that looks for patte...

     In the Digital Humanities Coursebook by Johanna Drucker, chapter six gave readers an understanding of information visualization and how important it is for readers to get a better understanding of the topic at hand. Chapter six also touches upon networks, and complex systems, and how important they are for creating relationships between data. Chapter seven of the Digital Humanities Coursebook talked about data mining and analysis. Data mining and text analysis is an important tool within Digital Humanities as it is used to understand text or literature in a deeper way. Chapter seven also talked about the issues surrounding data mining, and how those issues may make the data found inaccurate. Our other readings for this week touched upon distant reading and close reading and the arguments for both of them and their uses. The projects "Six Degrees of Francis Bacon" and "Yesterday, Today, Tomorrow" are visualization projects that use information visualization to g...