Department of Computer Science and Automation, Indian Institute of Science .
TWITMINER 2013 RESULTS
Finally we have some good news!!! After a really long evaluation process by PhD students at IISc and ML and business teams at Amazon, we have decided to declare the following teams as the winners of TwitMiner 2013:
Rank 1: Mani Kumar Adari from RGUKT, Nuzvid.
Rank 2: Sauradyuti Coondu and Anasua Mitra from Jadavpur University, Kolkata.
Rank 3: Ahmed Shabib and Arpan Gupta from PESIT, Bangalore.
Heartiest congratulations to the winners. Amazon.com will be offering internship to Mani Kumar Adari. The second and the third ranked teams will be eligible for prizes worth 10000 INR and 6000INR respectively. All the teams who uploaded their final submissions will also be offered participation certificates!
We are extremely sorry for the delay in declaring the results! We really appreciate the patience shown by everybody. We hope you all had fun mining tweets and got interested in Machine Learning! Please watch out for a few more updates in this portal related to the results, success stories and also the codes and writeups of the best team. Hope it'll be a learning experience as well.
We are looking forward to getting your valuable feedback HERE. This will help us to make the contest BETTER and BIGGER next year.
Teams which completed the final submissions, please fill up this FORM for particpation certificates(if you haven't done already).
SUCCESS STORIES
Mani Kumar Adari(WINNER of the Amazon.com internship) about himself:
"I, A. Mani Kumar is presently pursuing B.E, Computer Science and Engineering at Rajiv Gandhi University of Knowledge Technologies, Nuzvid. A valuable step after my 10th standard into RGUKT(www.rgukt.in) made me to make a long journey to get introduce to the world of Computer Science especially Machine Learning and NLP. The great initiation of RGUKT by taking merit students from rural areas gave me this great opportunity and made me to learn Computer Science topics pragmatically through "Learning by Doing" methodology."
His Success Story:
"I came to know about Twitminer programming contest on 9th March. Without delaying any second, I started designing classification model by summing my total knowledge in NLP and ML gained in my academics. I spent my complete time till the end of contest to improve accuracy. Finally I end up with Hierarchical classification model using Fisher Score based NB and SVM which can do classification with pretty good accuracy. Thanks to Twitminer contest organizers for providing a great interface to showcase my ML potential!"
Code and writeup:
People interested in learning from Mani's work in TwitMiner can download it from HERE.
FINAL LEADERBOARD
The final scores are now available below:
Rank | Team Name | Score |
1 | mani2348 | 97.155 |
2 | FireBird | 95.748 |
3 | HYDRA | 95.656 |
4 | Godfellas | 95.564 |
5 | Twanalysts | 95.473 |
6 | BEing | 94.983 |
7 | Turtle | 94.922 |
8 | Morpheus | 94.891 |
9 | jRh | 94.433 |
10 | Hellraisers | 94.402 |
11 | coders | 94.157 |
12 | peace | 94.065 |
13 | Robot | 93.423 |
14 | DoesNotMatter | 93.331 |
15 | viscrisn | 92.077 |
16 | AdaBoost | 92.077 |
17 | Gold_Miners | 91.649 |
18 | 2_bytes | 91.618 |
19 | Numb3r | 91.251 |
20 | Golamper | 90.945 |
21 | Miner | 90.578 |
22 | Beta_Bots | 90.456 |
23 | KGP_Learners | 90.364 |
24 | Team_Jinkchak | 90.272 |
25 | Maniacs | 90.242 |
26 | Bazinga | 90.211 |
27 | codeinsleep | 90.150 |
28 | Banyan_Learners | 89.997 |
29 | Stackoverflow | 89.966 |
30 | try_catch | 89.936 |
31 | heritage | 89.936 |
32 | Dark_Horse | 89.813 |
33 | Matrix | 89.599 |
34 | KGP_tweets | 89.538 |
35 | MAC_LEARN@IITKGP | 89.507 |
36 | Deagle | 89.507 |
37 | MS1 | 89.049 |
38 | tweet#01 | 88.957 |
39 | fundoers | 88.682 |
40 | 42 | 88.682 |
41 | skyfall | 88.651 |
42 | Pegasus | 88.590 |
43 | Twister | 88.498 |
44 | Tihana | 88.131 |
45 | Extractorz | 88.009 |
46 | The_Anonyminers | 87.764 |
47 | AustereSapiens | 87.244 |
48 | Cyber_Punk | 86.938 |
49 | plutos_pirate | 86.754 |
50 | Zen_Coders | 86.693 |
51 | Metal_Striker | 86.693 |
52 | firefly | 86.693 |
53 | BinaryMiners | 86.632 |
54 | kgpMiners | 86.173 |
55 | TheTeam | 86.020 |
56 | Useless_Productions | 85.959 |
57 | Miners1 | 85.959 |
58 | W-TransposePhi | 85.806 |
59 | Lazy_Learners | 85.500 |
60 | Inbetweeners | 85.347 |
61 | W00t | 85.102 |
62 | Vamshi | 84.980 |
63 | TextWreckers | 84.644 |
64 | TwitMiners | 84.154 |
65 | Vetri | 84.001 |
66 | TwMiners | 83.940 |
67 | Twitterati | 83.665 |
68 | Infominers | 83.114 |
69 | Zoid | 82.686 |
70 | DH@IITKGP | 82.533 |
71 | RocketShip | 82.319 |
72 | MachineTeachers | 81.034 |
73 | LetsTry | 80.942 |
74 | Arjunvmm | 80.697 |
75 | Prometheus | 74.518 |
76 | Sam | 73.876 |
77 | RoHaN | 73.509 |
78 | The_Unsinkables | 72.958 |
79 | Specialitas | 68.553 |
80 | kungfupanda | 63.261 |
81 | Underdogs | 61.578 |
82 | tweet-o-hola | 54.787 |
83 | minesweber | 49.648 |
84 | StupidAmigos | 0.489 |
85 | CASL | 0.336 |
FINAL SUBMISSIONS(CLOSED)
As a part of the final submission to this contest you are required to submit the following:
1. Predictions on the test data in the same file format as the validation data; click here for a sample file (in .txt format).
2. A brief writeup of your algorithm in the format prescribed here (in .pdf format).
3. Properly documented code along with a README file containing instructions to run the code (archived as a .zip).
Final submissions can be done HERE after login and will be allowed till March 15th 11:59PM IST (GMT + 5:30hrs). Multiple submissions are allowed but only the latest will be considered.
Final Submissions are CLOSED. Please mail us if you could not submit. Thanks a lot for participating!
TEST DATASET
Download Link: Test data
Please read the Instructions.txt file carefully. Also note that there might be noisy tweets included in the test dataset. But while calculating scores we wont consider them. The scores for the test data will not be displayed during submission. They will be displayed after the contest closes.
VALIDATION LEADERBOARD
Click here to access the upload form and the leaderboard.
While uploading your prediction labels on the validation data in a text file (.txt), use the following format:< tweetid label >
where the 'label' is either 'Sports' or 'Politics' assigned to the tweet with identifier 'tweetid' by your algorithm. Note that the prediction for each tweet must be in a separate line, with a single blackspace separating the tweetid and label. (Please be careful to not include additional blank spaces in the submitted file.)
Here is a sample file that you can look up for the format.
TRAINING DATASET
Download Link: Training and Validation data
Please read the Instructions.txt file carefully.
REGISTRATION
Registrations have been closed.