## Ciphertext Challenge II: The Challengening!

It's baaaaaaack!

In our first [ciphertext competition][1], we hunted the wilds of the '90s-era internet. This time around, we're exploring the dark slow-broadband-y wastelands of 2011, with the [Movie Review Dataset][2]. In 2011 most of the internet hadn't even been *invented* yet\*, so wow, you're in for a treat.

Again, [simple classic ciphers][3] have been used to encrypt this dataset. Your mission this time: to correctly match each piece of ciphertext with its corresponding piece of plaintext. Daunting! Also, there are some new ciphers in play this time, which will involve some meta-puzzling. Enjoy!

Swag prizes go to the first three teams to crack all four ciphers OR to the top three teams on the LB (in case the ciphers are not all cracked). Additionally, swag prizes will be awarded to the best *competition-related* kernels, in both visualization and cryptanalysis, based on upvotes.

Go ahead. Get cracking!

\* - This is not true.

## Acknowledgements
*Maas, A., Daly, R., Pham, P., Huang, D., Ng, A. and Potts, C. (2011). Learning Word Vectors for Sentiment Analysis: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. [online] Portland, Oregon, USA: Association for Computational Linguistics, pp. 142–150.* [Available here][4].


  [1]: https://www.kaggle.com/c/20-newsgroups-ciphertext-challenge
  [2]: http://ai.stanford.edu/~amaas/data/sentiment/
  [3]: https://www.kaggle.com/c/ciphertext-challenge-ii/data
  [4]: http://www.aclweb.org/anthology/P11-1015.