franny gaede (@mfgaede): #LearnAtDLF Text analysis workshop: starts with a quote from https://aclanthology.org/P99-1001.pdf, used in a variety of disciplines (bunch of citations!) #DLFforum
Twitter link: https://twitter.com/mfgaede/status/1579168675126730753
5 questions that text analysis can help you answer:
Question 1: what are these texts about? Can do word frequency analysis. Example: https://www.cameronblevins.org/posts/text-analysis-of-martha-ballards-diary-part-3/ #DLFforum
Question 1: what are these texts about? Can do collocation analysis. Example: https://doi.org/10.1093/notesj/gjz084 #DLFforum
Question 1: what are these texts about? TF-IDF analysis (term frequency-inverse document frequency analysis) #DLFforum
Question 1: what are these texts about? Topic modeling. Example: http://signsat40.signsjournal.org/topic-model/ #DLFforum
Question 2: how are these texts connected? Concordance. Example: https://www.loc.gov/item/31013167/, https://www.jstor.org/understand
Question 2: how are these texts connected? Network analysis. Example: Twitter suggested for you #DLFforum
Question 2: How are these texts connected? Network analysis. Example: https://journals.sagepub.com/doi/full/10.1177/20563051211055442 #DLFforum
Question 2: how are these texts connected? Bibliometric analysis. https://doi.org/10.1007/s10551-019-04129-4 #DLFforum
Question 3: what emotions (affects) are found within texts? Sentiment analysis. https://pmj.bmj.com/content/98/1161/544 #DLFforum
Question 4: What names are used in these texts? Named entity recognition. #DLFforum
Question 5: Which of these texts are most similar? Authorship attribution. Example: https://www.scientificamerican.com/article/how-a-computer-program-helped-show-jk-rowling-write-a-cuckoos-calling/ #DLFforum
Question 5: Which of these texts are most similar? Clustering. Examples: topic modeling is a specialized type! also: market segmentation, social network analysis, search result grouping, medical imaging, image segmentation, anomaly detection #DLFforum
Question 5: Which of these texts are most similar? Supervised machine learning. Examples: Image and object recognition, predictive analytics, customer sentiment analysis, spam detection (known/predetermined topics) #DLFforum