24 Matching Annotations
  1. Jul 2022
    1. The trends part of Voyant was interesting as it correlates with the arch of the story. “Pooh” is used fairly consistently throughout the story as he is the protagonist, while “Piglet” has a peak towards the middle as he is more of a side character. The use of “Christopher” also peaks more at the end as the front half of the story mostly focuses on his toys in their own world. Through Voyant, it is difficult to gain any real understanding of the actual plot of the book, but the “links” section of the program gives a clear arch of who the main characters are.

      I did the same book but I didn't see this correlation in the trends part. This is so interesting! It also shows that if you don't know the plot very well, you can miss out some analyses. I did see 'Pooh' used frequently throughout the segments of the book, but I did not realize how the side characters have a frequency increasing throughout the second half of the book.

    1. Where the 12 Tones of London is dedicated to capturing the characteristic sound of daily life in London, the Murder Map and Separados are meant to point out anomalies or hidden things – to show people things that they did not know existed in those places. The 12 Tones also integrated geographic data and demographic information of residents to divide London into clusters. This type of data is amenable to mapping, as is the real-time data about events tied to geographical points such as the murder map. 

      This is a very good point that I did not consider for the Murder Map. What both the Murder Map and The 12 Tones of London map do is integrate geographic data and demographic information and point out certain locations. In Murder Map, the locations are murder spots, and in 12 Tones of London, they are the most typical member in each cluster of council ward.

    1. Best to show specific locations (such as addresses) with customized colored markers for categories, plus text and images in popup windows.

      These maps are the most common map types that I have seen. These are used in tourist maps, college building maps, museum maps, and such. I have also used this kind of map using the Google My Map to relay information about Japanese American incarceration on the west coast, pointing out specific locations with text, website info, color, to show the development of Japanese towns.

    1. How have students’ attitudes and language toward women in different eras relating to gender discrimination changed and evolved at LACOL colleges? How do their public attitudes compare to their private ones?

      Yes this is a great question! I once read from the Amherst student newspaper that after Amherst became co-ed, there were a lot of sexual harassment issues. Especially, I remember a male student stating that because women now reside next door, they can't freely roam around bars and clubs. It would also be interesting to look at how student opinion changes, since there would be turning points not only in society but also in college that change their perspectives. For example, a sexual harassment incident at Amherst college changed the entire student body's perspective on reporting procedures and related administration.

    1. How are our individual communities responding to the different challenges posed by rising global temperatures and human-caused climate change? Is there a strategy to the response that can be inferred from maps? How are our smaller colleges  responding to these changing circumstances versus larger state schools?  What are the kinds of initiatives that are gaining momentum in communities? 

      These are exciting research questions and relevant to our campus lives. I'm wondering whether there would be a clear distinction between college initiatives versus small-scale or student-led initiatives. College initiatives can be mostly large-scale, funded by alumni/investors, and can involve architectural, and engineering elements more than student-led initiatives. Also sometimes, the college's response to climate change can be vastly different from that of individual students/communities. It would be interesting to understand how this group categorizes the community efforts and also look at state schools for comparison!

    1. Readers analyze and understand aspects of a text’s bibliographic and visual signification through paratextual, somatic, material, and institutional encounters with the text, long before reading a word. Readers analyze a text’s linguistic codes of syntax and semantics through a variety of cultural, disciplinary, and subjective frameworks and filters.

      From a novice's perspective, I always thought text analysis was using critical thinking skills and being able to understand and transliterate the hidden meanings or the author's intention. I didn't know there were so many different ways to look at the text. I did understand that material and institutional encounters with the text can be analyzed. But paratext and somatic encounters were new for me. Paratext, meaning the materials surrounding the main text, and somatic encounters with the text, I still have no clue. But it seems that text analysis has more than just writing and reading with the eye, especially noticing patterns, selecting or excluding certain parts, and relating the text to a larger social background.

    1. As shown from the video, the dataset currently was based on hand written dataset decades ago, later transcribed into a printed version and then the digital version. Each stage can induce errors due to the misunderstanding of the previous era’s researchers’ works. The next topic that I would wish to address would be the problem of archival silence.

      I like the fact that you referred to the video to address the unintentional/erroneous biases or misunderstandings of the previous researchers' works. It is interesting that in humanities and in archival work, many people and successive researchers/archivists contribute to the big data to make it smart data. That's why as you mentioned, we need to understand how transcribing from handwritten to digital versions can include some mistakes.

  2. Jun 2022
    1. On a higher level, digital data are usually represented and processed in data structures that can be linear (for example arrays and matrices, like lists and tables in a data sheet), hierarchical (with a tree-like structure in which items have parent-child or sibling relations with each other, as in an XML file) or multi-relational (with each data item being a node in an interconnected network of nodes, as in graph-based databases).[5] Some additional distinctions are important. For instance, there is structured and unstructured data as well as semi-structured data. Structured data is typically held in a database in which all key/value pairs have identifiers and clear relations and which follow an explicit data model. Plain text is a typical example of unstructured data, in which the boundaries of individual items, the relations between items, and the meaning of items, are mostly implicit. Data held in XML files is an example of semi-structured data, which can be more or less strictly constrained by the absence or presence of a more or less precise schema. Another important distinction is between data and metadata. Here, the term “data” refers to the part of a file or dataset which contains the actual representation of an object of inquiry, while the term “metadata” refers to data about that data: metadata explicitly describes selected aspects of a dataset, such as the time of its creation, or the way it was collected, or what entity external to the dataset it is supposed to represent. Independently of its type, any dataset relevant to research represents specific aspects of the object of scrutiny, be it in the natural sciences, the social sciences, or the humanities. Data is not the object of study itself, but “stands in” for it in some way. Also, data is always a partial representation of the object of study. In some cases, however, it is our only window into the object of study. Still, this “disadvantage” of partial representation is small compared to the the fact that digital data can be transformed, analyzed, and acted upon computationally.

      I'm actually surprised to see that the concept of data in humanities is similar with that in the marketing field. From this summer's internship, I have learned about search engine optimization, which prioritizes data as a door to understanding the language of search engines. To optimize nontext components of webpages, the structured data and metadata are used in coding to mark up relevant content and increase search engine visibility. Especially using extensible markup code(XML) or structured data helps identify specific types of content. For me, it is clear that data, whether it be in humanities or digital marketing, can be used for the visibility of particular objects.

    1. For example, we are told nothing of the author of the journal: was a student or professor? Or someone not affiliated with Swarthmore College? Why did they write the journal in the first place and why for only a year? Was it one person writing the journal or multiple people? And what served as the deciding factors for what counted as a homophobic event and what didn’t?

      I liked the introduction starting with defining what archival work is, then moving on to the metadata that can unpack information of archives. It also brings up curiosity that there is no author information about the journal because, for most academic journals, the publication affiliated stakeholders or collaborators are always noted. A valid point also from the blog post is that since it dated from 1986 to 1987, there might not have been a clearly defined medical term and specifications for homosexuality, homophobia, and related people's subcultures.

    1. Klein - The Image of Absence- Archival Silence, Data Visualization, and James Hemings.pdf

      P 663. This striking instantiation of archival silence illuminates the concerns that course through the archive of the antebellum United States. (I added annotations on the title since I could not annotate directly on the text) Comment: The digital humanities that shed light on archives show that not only documents have power inherently that leaves a legacy of the privileged, but also in the making of archives, the act of revisiting the documents, such as the moments of fact creation, fact assembly, fact retrieval, and retrospective significance may be a silencing one. Especially here, the featured antebellum archives show distinctive dynamics of gender, social hierarchy, and social vocabulary that scholars may not notice the archival silences.

    1. No one was keeping detailed records of these deaths, nor was anyone making even more basic information about what had happened publicly available. “We couldn’t get that information,” explains Gwendolyn Warren, the Detroit-based organizer who headed the unlikely collaboration: an alliance between Black young adults from the surrounding neighborhoods and a group led by white male academic geographers from nearby universities.1 Through the collaboration, the youth learned cutting-edge mapping techniques and, guided by Warren, leveraged their local knowledge in order to produce a series of comprehensive reports, covering topics such as the social and economic inequities among neighborhood children and proposals for new, more racially equitable school district boundaries.

      This paragraph reminds me of my personal experience of working with social enterprises. When I was in charge of a corporate social responsibility project, I had to do marketing but there was no available data of the company's csr activities. Same way as the young adults did, I had do gather data from local welfare centers and scraps of data from the company database that proved that the company is really a social enterprise and not whitewashing its brand. It seems that collaboration between local youth and companies can make progress in the digital humanities field in various sectors and methods.

    1. Table 1.1: The four domains of the matrix of domination14

      This table really helps to structure the domination, and also gives me a better understanding of the power structure.

    2. The complexity of these intersections is the reason that examine power is the first principle of data feminism, and the focus of this chapter. Examining power means naming and explaining the forces of oppression that are so baked into our daily lives

      I recently learned the same issue in archives as well, Amherst college archives consists of mostly traditionally white men's history, so the archivist was telling us to be aware of the power structure.

    3. —and because she was Serena Williams, twenty-three-time grand slam champion, they complied.11 “If I wasn’t who I am, it could have been me,

      Sad and angry that just because the privilege of an individual could make things happen that others could not experience.

    4. there was still no national system for tracking complications sustained in pregnancy and childbirth,

      quite shocking that there wasn't a national system in 2018.

    5. On Williams’s Instagram feed, dozens of women began posting their own experiences of childbirth gone horribly wrong.

      Great example of instagram # projects and initiatives, it reminds me of the recent Roe v. Wade protests on instagram about reproductive justice.

    1. The digital humanities seems another space within the academy where the divide between making and interpreting might be bridged in productive ways.

      Yes, it may provide a novel path that integrates both perspectives, seems hopeful.

    2. not the specific subfield that grew out of humanities computing but rather the changes that digital technologies are producing across the many fields of humanist inquiry.

      Would these two fields be rather separated? I feel like this could be a chicken or eggs question.

    3. And there are initiatives that are designed to help digital humanities archives and projects become interoperable and to facilitate the peer review of these projects

      Would like to know further about these initiatives, I think these are really important efforts to make humanities projects more accessible and intersectional to other fields.

    4. more palatable to humanists

      Why is it so? Exactly what aspect of 'computing' makes it less palatable than 'digital humanities'? Is it the uncomfortableness of having to communicate with a totally different field, or the uncertainty in the 'computing' field since it is an everchanging field?

    5. prospectively titled “A Companion to Humanities Computing.” Blackwell wanted a title that might appeal to a wider range of readers and so proposed “A Companion to Digitized Humanities.”

      I'm also curious about the word computing and digitized, they have completely different notions. Computing gives a more computer oriented view, while digitized gives a more archival and accessible view towards humanities. Based on these words and categories, I wonder if digital humanities range from humanities from a computer science perspective to humanities from a very traditional perspective. For example, would autonomous car engineers learning about ethics and morals be considered to be involved in digital humanities?

    6. the kinds of questions that are traditional to the humanities, or, as is more true of my own work, ask traditional kinds of humanities-oriented questions about computing technologies.”

      I guess 'traditional' would also mean fundamental, since in the 21st century there has to be inevitably unconventional and newly emerging questions and researches to the humanities.

    7. every “What Is Digital Humanities?” panel aimed at explaining the field to other scholars winds up uncovering more differences of opinion among its practitioners. Sometimes those differences develop into tense debates about the borders of the field and about who’s in and who’s out.

      It makes me question what is so important about setting boundaries? Is it about the field's authority, or narrowing it down so that there is a consensus or clarity?

    8. by the use of social media, particularly Twitter, at the Modern Language Association (MLA) convention and other large scholarly meetings.

      I didn't know that Twitter was an immense influence in the MLA convention. I rather thought Instagram as a more prominent example of the use of social media, since now we can see a lot of humanities related articles/insights/projects always posting on instagram and asking for support and traffic