To-do notes archive.
to-do (4/7)
- draft methods and results
- tables for greatest component
- figures of k-cores in Gephi
to-do (3/17)
- clean the 3 combined datatables (i.e. article_neg.csv)
- keep track of knowledge representation issues
- unraveling k-cores in Gephi: minimum set of edges that causes the k-core to unravel (how to beliefs change?)
- assigning edges to categorical relationships (i.e. causative...)
to-do (3/3)
- spectrum of sentiment (highly positive to less positive, etc.)
- try manually separating by argument topic: what are people talking about
- check out CINET for targeted node removal (Maleq)
- K cores
- start working on union of network graphs (grouped by sentiment)
to-do (2/25)
- make box plots per sentiment
- some other nice figs explaining what the data means
- fix high centrality node data
- check out k-cores
- try manually separating by argument topic
- start working on union of network graphs (grouped by sentiment)
to-do (2/18)
- finish jupyter notebooks for pd export
- look at distribution of aggregate measures
- look at clusters of networks for terms with highest centrality
- cluster articles by overlapping terms
to-do (2/11)
- finish all data
- list all network metrics to run + interpretation
- create jupyter notebook for analysis
- export networkx output into pandas dataframe