Ny times speed dating
Using her natural strengths, we focused on subverting the cliché that women are inferior drivers.
For Mustang Speed Dating, we wanted to show a female stunt driver in a Ford being her authentic self, using skills that break the stereotype that women should be demure, or that women aren't great drivers.
Predicting the number of upvotes a comment will receive using the feature `recommendations` as the target variable.
With enough training set for the model, we can make a guess of how a hypothetical comment on a certain topic will be received by the community of NYT readers\u0027 and this can be considered a tool to gauge public opinion.
Per the strategic directive to resolve tensions surrounding gender-based cultural perceptions of driving, this campaign was an absolute success.
Analyzing behaviors of the top commenters such as which topics they most likely comment and the sentiment analysis of the comments.\n\n### Data collection\n\n The [python package here](https://github.com/Aashita K/nyt-comments) written to supplant this dataset can be used to retrieve comments from a customized search of the NYT articles concerning a specific topic, for example - Iraq war or Obama Care - in a given timeline.Female drivers are outnumbering male drivers for the first time ever—and Millennial-generation female buyers are outpacing Millennial male buyers by 53 percent.The demographics of the automotive market are shifting faster than traditional marketing can keep pace.This data can serve the purpose of understanding and analyzing the public mood.\n The [exploratory kernel here](https:// can be used for a review of the features of the dataset and the [NB-Logistic model kernel](https:// for predicting NYT\u0027s pick can be used as a starter for building models on a range of ideas, some of which are:\n\n1.
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Predicting how likely it is for a comment to get replies (using `reply Count` feature as the target variable).\n5.