Closed mayunk264 closed 4 years ago
QUESTION THAT MAYUNK IS ADDING:
So, how do users' and critics reviews change over time?
QUESTION THAT SEN IS ADDING: What are the common words and adjectives in low and high reviews? And further analyzing user reviews’ sentiment analysis.
Assignment 2 - ‘Changes to be made and why’ checklist. TO DO: Wednesday night
Add Sen’s question - word analysis on low and high reviews. Why? The world analysis in report gives us an overall picture of the ‘negative’ and ‘positive’ of the report. But it isn’t specific enough - what specifically do users not like about the game (word analysis on low-end reviews); and what do they really like the game (word analysis on high-end reviews).
Add Mayunk’s question - how do reviews change over time? The game (having played it myself and based off team brolga’s analysis) is a slow burn - how can a reviewer really get a full understanding of the game in the days immediately after its release? So, is there a clear trend to how the reviews change week-to-week? Are there any outliers that are worth looking at?
Add table of contents per Di’s advice
Spelling and grammar check
Update references.bib
Convert figure 4.1 into percentages
Fix up the figure references for entire report
Figure 4.2 and 4.3 are potential duplication of information - delete figure 4.2 and include a sentence on how personality types exclusively associate with gender.
Delete data dictionary - it is long and tedious. The tables listed are long and without context, not necessarily important for the viewer to see. Provide commentary on where to find data dictionary info if the viewer requires it.
Tables 4.1 and 4.2 are probably unnecessary information - we have an idea of the number of items in a category and the respective price ranges. We think that there is enough info and maybe a simple sentence on the most expensive and least expensive item will suffice here.
Delete figures 4.6, 4.8 and 4.9. This information is interesting but it is too broad and will in some ways duplicate Sen’s analysis. Sen’s analysis will focus specifically on extremely negative and extremely positive reviews as opposed to the entire body of user reviews.
Run through report with principles from Week 4:
Run through report with principles from Week 5:
Run through report with principles from Week 5:
Forgot to add:
Really beautifully done!
On 15 Sep 2020, at 2:28 pm, mayunk264 notifications@github.com wrote:
Forgot to add:
Add conclusion Run through marking rubric Modify question section to correspond with deleted/added analysis — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub https://github.com/etc5521-2020/assignment-1-brolga/issues/4#issuecomment-692456098, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAB52BY35NZWZGLXCALPAR3SF3UNVANCNFSM4REQ2ORQ.
Di Cook visnut@gmail.com
As per zoom chat with Sen, keep figures 4.8 and 4.9
Please note: the following is a summary of a brainstorm session that Sen and I had over Zoom
MINOR CHANGES TO MAKE:
Change the title in the YAML. Use inline R codes so the numbers are entered by code. Convert figure 4.1 into percentages. Fix up the figure reference for 4.1 and 4.2. Figure 4.2 and 4.3 are potential duplication of information - try and combine those plots. Add interactivity to figure 4.8.