This week’s lesson has probably been my favourite so far as we got to explore many tools that analyse texts, documents, and data! Not only are these useful in digital heritage but also a lot of what was discussed today can be used for my other classes.
Read more under the cut!
We started off looking into tools to track trends using Tim’s QueryPic and Google’s Ngram. QueryPic is a way to explore Trove’s digitized collection of newspaper trends and topics over time by searching words or phrases. Though it was great for getting a broad idea on trends, it only plotted the number of articles per year over time and apparently it also includes Trove tags, which is a reason to remain skeptical as it could alter the results. Similarly when looking at Google’s Ngram (the letter ‘n’ stands for number) there are some issues that could affect the results such as case sensitivity and the inability to refine results. Ngram looks at the usage of words in books over a period of time. Both tools, though great for quickly identifying trends, have their downfalls and as a result I would probably only use them as a starting point for research rather than a quotable figure.
I also really enjoyed using Voyant (the owl logo was quite cute too) and Wordcounter. Voyant analyses the content of a text that can then be refined to compare and contrast details within, while Wordcounter sorts a text to show the most used words, bigrams (two word phrase), and trigrams (three word phrase). We used both tools to analyze Prime Minister’s speeches however these tools could also be useful in a digital heritage context to identify trends in newspapers and literature.
Finally we looked at Overview, a tool that breaks down topics in documents. Though we looked at it in a digital heritage context I would definitely use this tool for my journalism units, however it seems a bit difficult to use and would require practice.