Precog: The Phenomenon

A normal afternoon day, with the heat scorching its way through to every one of our rooms at NIT Trichy. I was scrolling through my mails, as usual. However, today something caught my eye. A particular mail from my ACM student membership subscription that looked like this:

I am a huge fan of Social Networks research by the way. Right from its theoretical aspects – centrality measures, the small world phenomenon, etc.. up to its more applied research aspects – mining important data from Online Social Media, creating core systems that constantly evolve and adapt using the humongous data obtained from social networking sites, OSM Analysis has never failed to amuse me.  So the moment I read and researched about Dr.PK, I knew he was one professor anyone would really desire to work with, and that this is the kind of work I would like to pursue.

From looking through the window, To being welcomed inside

The most significant characteristic about this group is that, Precog means business. They are a bunch of researchers who have made their mark all over the world simply by doing what they love, bounded by no restrictions whatsoever.  This is what made this research group an even more desirable organization to be a part of. The urge to be a part of this only increased every day ever since I read about it. I applied to PK soon after, and after a structured and elaborate induction process, on another sunny afternoon, a mail popped up in my inbox.

I got my offer letter.

“Make us proud, by making yourself proud.”

 PK’s words from his mail to me lingered in my mind as I sat in the CERC lounge on my first day, waiting for my mentor and PhD scholar Prateek Dewan to brief me on my project. Prateek came, we exchanged pleasantries and got down to business immediately. The words Prateek said:

“You’ll be working on the Image Analysis domain for this summer. In particular, you will be working on Extracting the Sentiment (Emotion) from an Image. All the Best.  Always here to help you if you need anything.”

The meeting lasted 10 minutes. I was taken by complete surprise. The most image analysis I had ever done before was to see if an image on my Facebook news feed was worthy of a like or not. 😛

But that’s the very beauty of Precog. Remember how I told you about there being no restrictions whatsoever here? This was a standing example of that. My objectives were clear. But I had COMPLETE freedom to pursue any path I wanted to get the job done by the end of the summer. [1] Thus said, I embarked on a journey of pure knowledge discovery and fun.

 The Liam Neesons of Precog

Hardly a few weeks had gone by during my internship, and I was LOVING it here. My work was going on a smooth pace. I was slowly getting a hang of the state-of-the-art in Image Analysis and constantly surveyed relevant literature. Of course, I was nowhere near even charting a course to achieve my goals for the summer, but I knew I was on my way. I had lots of motivation and initiative, but at regular intervals of time, I also needed direction, perspective and feedback. Here is where I introduce the Liam Neesons of Precog, or as PK calls them, the “Pillairs” of Precog. Why Liam Neeson though? Well, that’s because every member at Precog has a “very special set of skills” that make them really powerful and strong in their domain of computer science. Each member here specializes in something unique, working on a completely different problem altogether but with just one common cause – to help the common man and do social good. Needless to say, this eclectic mix turned out to be a gold mine of information for me. Every interaction I had with each one of them, there was some take away from it. The weekly brainstorming sessions we had, discussing important and high-impact papers were a huge repository of information too.

“In Precog, data and information were not just something we worked on, but something we gained too. “ [2]

But none of this would be complete without mentioning the pioneer behind it all, PK. PK always kept us on our toes by pointing us to interesting articles/research/technology as it released and encouraged us to probe more into each one of them. Perhaps the one person with the highest motivation levels in Precog is PK himself. There was never a dearth of motivation in the lab. PK always made it a point to keep throwing new ideas in the air, and if something seemed viable, included everyone in bringing up a solution. He had this knack of just sparking a small thought in our minds and leaving it at that. That thought would transform into an idea, the idea into something else until it lead to some really big solution for a confounding problem. His heartfelt and personalized greetings, wishes and guidance will put you in utter disbelief – how could such a busy and accomplished person still have time for each one of us and care about each of us and our projects with such attention? All of this made me grow very attached to PK and the group as a whole, to the extent of worrying about my fast approaching last day. 

The Technical Details

Keeping this part very short, with constant guidance from my mentor, we were able to propose two novel architectures – one to find the expression of all faces present in an image using special facial features and the second to classify an image as a whole as positive or negative based on a deep network architecture. Never had I thought I would be successful in establishing a working model for this if not for the constant support of PK, my mentors and all members of Precog as a whole.

 The Fun Parts!!

Apart from all the rigorous working, pulling all-nighters and meeting deadlines, the fun quotient was also extremely high here at Precog. We went on a lot of outings, right from nearby ice-cream desert shops to malls in Noida. Recounting all those experiences now, as an intern, I felt like I experienced almost everything there is to experience at Delhi. How much ever Precog works, they have fun equally or even much more! Ultimately, be it a tough problem to crack, or a big pizza to finish, we did it as a group, together. 😛

 We go live in 5…4….3…

As a result of all the collective hardwork of the Image Analysis team I was a part of, Helix, an Image Analysis tool was born. I now reminisce over my internship and think about how the journey was as wonderful as the elated feeling I get when I see a small part of my work being used by live users everyday. The fun discussions I had with the PhD scholars, the homely feeling I got every time I entered the lab, all the fun I had with my newly found friends, and of course all the knowledge I gained – everything was worth it at the end. What I was when I started, and what I am now.  It was then that I knew, this was the true goal of my internship. [3]

With a sense of fulfilment and content, my internship was complete. Not a day goes by, when I don’t see the Precog sticker on my laptop and recount the wonderful experience I had at Precog.

A pic of me with my mentor and close friend, Prateek:

The Head Fake

No Precog blog is complete without Randy Pausch’s wisdom being in it. As Randy describes it, A head fake is something that we are made to do, but its purpose is completely different from what is presumed. Observe above in the blog that I have put the numbers [1], [2] and [3] at several points. Those were the head fakes of my internship.

[1] This internship of mine was not solely aimed at the result alone. The freedom I got to pursue my desired path throughout the internship lead to a huge inflow of ideas and thoughts in my mind. This refined my thinking, not just for the problem, but for everything else too. I wasn’t fed fish. I now knew how to fish. This was my first head fake.

“I knew how to fish.”

[2] By the end of the summer, I had more skills than I could possibly have expected to get just by working on my problem alone. This is completely attributed to the sessions we had, information we shared and discussed.  I had so much more skills now that I could confidently add to my kitty than I could imagine. This was my second head fake.

“I too got a special set of skills.”

[3] Finally, I got a family. A permanent set of close friends, and an evergreen connection to Precog, no matter where I proceed further in life. This was my third head fake.

“Once a Precog-er, always a Precog-er.” 

For all the prospective future students reading this blog:

The final head fake: The blog was not just to pen down my experience at Precog. It was to motivate you guys to come and experience the phenomenon that is Precog. 🙂

If you are interested in #PrecogSummer 2017, please do checkout http://precog.iiitd.edu.in/openings/PrecogSummer/

This is Why I Love My Job: Students are the backbone of Faculty life!

It is that time of the academic year when convocation at IIITD just got done (Aug 27, 2016), and all graduating students and Research Associates have moved on to the next phase in life (started work, grad school in India, grad school outside India, etc.). Below is the picture from the convocation #IIITDConvo5! Convocation message by the Chief Guest Mr. Naveen Tewari, Founder & CEO InMobi, “Do what you love” “Have faith” “Crazy is good”!

There are a few reasons why I love my job: (1) majority of the times, I am surrounded by young, energetic, and smart people; (2) most students are successful in doing whatever they are doing, so there is a lot of positive energy and excitement around me; (3) of late, I have started seeing students coming back with an incident or gyan that I gave at some point in time during their interactions with me which has helped them and this feels good! As a faculty, I would like to believe that I play some role (hopefully, positive) in shaping the students’ academic life and sometimes beyond.

Below is the list of students (arranged in alphabetical order of last name) who have spent significant amount of time working with me and / or I have written Letter of Recommendations (LoRs) for their admissions / job and are now moving onto the next page of life with full zest and enthusiasm.

  1. Megha Arora: Has taken many of my courses, did her UG thesis work with me. She received the Chancellor’s Gold Medal for the batch of 2016. Starting her Masters’ in Computer Science program at Carnegie Mellon University (my alma mater!).
  2. Sonia Dalal: Has taken some of my courses, and did an independent project with me. Starting at Bloomberg London.
  3. Shashank Gautam: Has done some of my courses, did his UG thesis on MeriAwaaz with me. Received the Best BTP Award in Entrepreneurship! Joining KPMG in Delhi.
  4. Sonal Goel: Has taken some of my courses, completed her M.Tech. thesis with me, “Image Search for Improved Law and Order: Search, Analyse, Predict image spread on Twitter.” She is continuing to work with me as a Research Associate.
  5. Shantanu Goel: Has taken many of my courses, including Designing Human Centred Systems, and Privacy and Security in Online Social Media. Started his Masters in Management at Singapore Management University.
  6. Shrey Gupta: Has taken some of my courses, and completed his UG thesis with me. Started MBA at Faculty of Management Studies, Delhi.
  7. Ananya Harsh Jha: Ananya is taking a break of one seemster to work with a startup enabling enable drug discovery for different strains of cancer.
  8. Gandharv Kapoor: Has taken many of my courses, including Designing Human Centred Systems. Starting Masters in Computer Science at Stony Brook University.
  9. Aarushi Karnany: Has taken many of my courses, including Designing Human Centered Systems and did an interesting Independent project with me. Starting Masters in Computer Science at University of Florida.
  10. Rohan Katyal: Has taken many of my courses, did his UG thesis work with me. Starting his Masters’ in Human Computer Interaction at Georgia Tech.
  11. Mudita Khurana: Graduated from IIITD in 2013, spent time in the industry and will be starting her Masters’ in Information Systems at Heinz College, Carnegie Mellon University.
  12. Jayasi Mehar: Has taken multiple courses with me, did her UG thesis work with me, co-founded Backpack, a learning management system that we built. Will be starting MS in Computer Science at University of Illinois at Urbana-Champaign.
  13. Pradyumn Nand: Received his M.Tech. from IIITD, completed his Masters thesis with me. Joined MakeMyTrip.com recently.
  14. Mansi Panwar: Took some of my courses, completed her UG thesis with me on MeriAwaaz. Received the Best BTP Award in Entrepreneurship! She’s managing MeriAwaaz now.
  15. Gandeevan Raghuraman: Graduated from College of Engineering, Guindy / Chennai in 2015. Spent some time with me as Research Associate, and will be starting his Masters’ at INI, Carnegie Mellon University.
  16. Hareesh Ravi: Spent close to 2 years with CERC, Cybersecurity Centre @ IIITD. Will be starting his Ph.D. work with Dr. Mubbasir Kapadia in the Computer Science Department at Rutgers University, working on problems in computer vision.
  17. Srishty Saha: Has taken many of my courses and did her UG thesis work with me. Will be joining the Masters’ in Computer Science program at UMBC.
  18. Yatharth Sharma: Spent more than a year as a Research Associate with us; he is a UG from JIIT. Started Masters’ in Computer Science at Arizona State University.  
  19. Archit Srivastava: Started working with me from May 2014, was working with me even during the semester. Graduated with B.Tech. from NIT Durgapur in 2016. Started Masters’ in Computer Science at University of Southern California
  20. Vedant Das Swain: Has taken many of my courses, helped me with many designs that I have made in the last few years. He’s starting his Masters’ in Human Computer Interaction at Georgia Tech.
  21. Aakriti Tayal: Completed her UG thesis with me.

Below is picture with most of the above mentioned students. I sincerely thank each one of them in adding some colour in my faculty life!

I wrote LoRs for a few other students who received graduate school admissions and jobs this year, these are students who may have taken only one course with me or one Independent project with me.

It is very satisfying to see students achieve what they want to achieve and even more satisfying to feel that as a faculty we play a role in their achievements.

Here is a pointer to the blog that I wrote in 2014 about the graduating students and their next steps http://precog.iiitd.edu.in/blog/2014/06/students-are-the-dna-of-faculty/ Many of them are successful in what they are doing, some are doing great things now!

First Time’s the Charm

I had to select courses to register for in the Winter semester of 2016. One of them, DHCS, caught my eye but I was a bit hesitant to register for it. My friends had to persuade me to take DHCS instead of another course just so that we could form a group to do the course project! When I attended the first lecture of DHCS, I knew I would love the course. I was not proven wrong. The assignments were enjoyable, though challenging. I learned the design process that is followed in order to create usable interfaces. I faced obstacles and jumped high over them. My interest in HCI increased tremendously.

BBI fun with group members

The course had a showcase event to present our final project to a team of judges. This showcase was a unique experience for me since we were expected to not only present the mobile app but to market our mobile app to the judges. The teams went all out in this final presentation and it was heartening to see the effort we all put.

Preparing for BBI

When I registered for DHCS on the cold December night, little did I know that I was registering for much more than a course. Taught by PK, the course was everything an HCI student could dream of. I continued my association with PK over the Summer through an internship.

I worked with Niharika Sachdeva on analyzing Policing and OSM. Niharika Ma’am is an amazing mentor. I learned several new techniques and analysed several papers as research for my project. Her feedback was insightful and aided me in making my project more streamlined. She asked several questions to which I had no answer. This made me read about the concepts behind my work. In the process, I learned several new things.

Another highlight was meeting all the Precogers, as we call ourselves. (Yes, I am a Precoger now!) The amount of intelligence in the room tangibly increases when all the Precogers are together. We have several interactive sessions where everyone gets together and talks about their project or any new ideas they have had. The insights provided by the Precogers give a fresh perspective to the problem we are working on. This system of feedback ensures we stay on the top of our game.

A few of the Precogers

To be a part of PreCog is to be inspired. I have loved my journey here so far and I look forward to several more memorable experiences.

A Picture is Worth 32.33 Words: Importance of Analyzing Images on Online Social Media

Do you remember the last time you rushed or saw any one rush to get an “autograph” of a famous personality? No, right? Because those days are long gone. Today’s generation believes in taking a selfie instead. And why not, digital media is forever, or at least, it can easily outlive a piece of paper with an autograph! There is an explosion of data that is generated on the Online Social Media (OSM), we see 422,340 tweets on Twitter, 3.3 million updates on Facebook, 55,555 pictures uploaded on Instagram every second [1]. In the recent past, with the updates, large fraction of it is images / pictures; one analysis shows that 1.8 billion photos are shared on Facebook, Instagram, Flickr, Snapchat, and WhatsApp every day [2]. It is also found that updates with images increase the engagement of the posts, like [3] shows 18% more clicks, 89% more favorites, and 150% more retweets when the tweet has an image compared to only text updates. Another article reports 93% of the most engaging posts on Facebook have an image [4]. Researchers are also studying what makes an image popular on networks like Flickr [5].

In last few years there have been many academic papers, technologies in real world all looking at this growth of content and analyzing them; we see most of them analyzing only the textual part of the content. Here is a non-comprehensive list of publications in some of the top tier conferences in this space; all of these papers look at content generated in English [6 – 20]. Some researchers are also looking at studying the sentiment and textual characteristics of non-English content on OSM [21 – 27]. Languages include, Farsi, and Hindi.

I have been curious for a little while now about non-textual content on OSM; some of my recent interest has been to look at images and videos on OSM. I recently had my student Sonal Goel investigate images on OSM, she completed her Masters thesis “Image Search for Improved Law and Order: Search, Analyse, Predict image spread on Twitter” where she predicted the virality of images on OSM using tweets from multiple events. Prateek Dewan, my Ph.D. student and I have been playing around the broader topic of images and OSM. We believe that the inferences that we draw from textual analysis can be different from the analysis done with images from the same posts. For example, textual analysis done in Hurricane Sandy [28] and Boston Marathon [29] could have classified the posts with images (along with text) to be legitimate, whereas, if we analyze the images itself it may be fake. Below is a fake image which went viral during Sandy, but textual analysis for the posts with these images could have leaned towards credible content.

 Sentiment analysis of the OSM content is used to make decisions on the pulse of citizens, customers, etc. Sometimes the sentiment of the textual content is very different from the images posted with the text. Below image was posted with the content “Thank you Piers Morgan for speaking truth. #PrayForParis #MuslimsStandWithParis“ [30] Text analysis will give positive / neutral sentiment, while the content from the image attached with the post is negative. We found other examples to substantiate this point, post being negative and image being more positive [33, 34] and post being positive and image being more negative [35].

Just to test our hypothesis of how much information is spread through images, we analyzed some events for which we have been collecting data. Below is the table which shows data for 9 events; consistently we see that on average about 20 – 25% of the content has only images without text. In most of the analysis that is done now with textual content will miss this information. In one of the event that we are analyzing now, we were able to extract text from 8,200 images; these images were posted on OSM with no text. To understand the amount of text that are shared through images, we got images annotated and using Tesseract OCR [31], we were able to get 1,030,471 words from 31,869 images.

Column “with text” refers to the number of posts containing the “message” field as returned by the Graph API. This field contains the status / text message posted by the user. The “with image” column represents the number of posts where the “type” of post is “photo.” Facebook automatically determines this “type” while a user is composing a post. This field is assigned to ALL posts, and can take up one of the following values: link, status, photo, video, offer [32]. This makes column “text and image” an intersection of previous two columns. Similarly, “image and no text” is a subset of column “with image”, and “text and no image” is a subset of column “with text.” All values in the table in parenthesis is percentage value.

Event Total posts Posts with text  Posts with image  Posts with text and image  Posts with image and no text  Posts with text and no image 
AirAsia flight missing 2014  22,820 6,868 (30)  10,192 (44)  538 (2) 9,654 (42) 6,330 (28) 
Cricket world cup 2015  20,960 17,217 (82) 7,463 (36) 5,756 (27)  1,707 (8)  11,416 (54) 
Ebola outbreak 2014 67,453 28,030 (42) 12,386 (18) 1,553 (2) 10,833 (16) 26,477 (39)
Euro cup 2016 109,189 77,355 (71) 61,119 (56) 40,518 (37) 20,601 (19) 36,837 (34)
Wimbeldon 2015 111,417 80,469 (72) 52,756 (47) 37,862 (34) 14,894 (13) 42,607 (38)
Paris attacks 2015  131,548 78,803 (60) 75,277 (57) 32,861 (25) 41,416 (32) 45,942 (35)
Malasiyan MH17 crash  2014 22,490 5,270 (23) 2,947 (13) 316 (1) 2,631 (12) 4,954 (22)
IPL8 cricket 2015  48,329 31,526 (65) 19,116 (40) 9,251 (19) 9,865 (20) 22,275 (46)
Gaza unrest 2015  31,537 10,142 (46) 6,157 (20) 1,716 (5) 4,441 (14) 8,426 (27) 

Given this growth of images and pictures on OSM, and less work done on topics related to OSM & images, there is a great scope for contributing in this domain. There are full-fledged and dedicated traditional conferences like IEEE International Conference on Computer Vision, International Conference on Machine Learning (ICML), and IEEE Conference on Computer Vision and Pattern Recognition (CVPR) which look at images. There needs some knowledge transfer from these classic domains to OSM. It may also be the case that, in the past, image analysis was not as advanced as it is now, so, advancements in image analysis, including neural networks now makes it possible to do some really cool image analysis which could have been difficult or impossible to do it earlier. Given the large amount of data on OSM, and with advanced image analysis techniques, we should be able to answer some very exciting research questions.

Some specific topics and problems that I think that will be interesting in this space of OSM and images (these are just my random thoughts and they are non-comprehensive):

  • Spread of untrustworthy / Mis-information on OSM through images
  • Leakage of personal information like current location, etc. through images on OSM 
  • Leakage of sensitive information like DOB, gender, etc. through images on OSM

If you are interested in keeping updated about our activities at Precog, you can visit our website or our Facbeook page If you have any suggestions or ideas to explore in this direction, feel free to write to me.

Acknowledgements: I thank my brilliant students Prateek Dewan, Niharika Sachdeva, Indira Sen, Kushagra Singh, Megha Arora, Hemank Lamba, and Varun Bharadhwaj for helping with putting together these thoughts / some numbers / analysis in this post. Thanks to all members of Precog group where the idea of studying images and trying it out from different perspectives started.

References

  1. http://www.smartinsights.com/internet-marketing-statistics/happens-online-60-seconds/

  2. http://www.businessinsider.com/were-now-posting-a-staggering-18-billion-photos-to-social-media-every-day-2014-5

  3. http://www.adweek.com/socialtimes/twitter-images-study/493206

  4. http://www.socialbakers.com/blog/1749-photos-make-up-93-of-the-most-engaging-posts-on-facebook

  5. https://people.csail.mit.edu/khosla/papers/www2014_khosla.pdf

  6. Pollyanna Gonçalves, Matheus Araújo, Fabrício Benevenuto, and Meeyoung Cha. 2013. Comparing and combining sentiment analysis methods. In Proceedings of the first ACM conference on Online social networks (COSN ’13). ACM, New York, NY, USA, 27-38. DOI=http://dx.doi.org/10.1145/2512938.2512951

  7. Tomer Simon , Avishay Goldberg, Limor Aharonson-Daniel, Dmitry Leykin, Bruria Adini. Twitter in the Cross Fire—The Use of Social Media in the Westgate Mall Terror Attack in Kenya, Plos-One.

  8. Saritha SK, Devshriroy D (2013) Semantic Orientation of Sentiment Analysis on Social Media. International Journal of Computers & Technology 11 (4) 2401–2409.

  9. Munmun De Choudhury,Scott Counts, and Eric Horvitz.2013. Predicting Postpartum Changes in Emotion and Behavior via Social Media. In Proc. CHI ’13

  10. Munmun De Choudhury, Scott Counts,Eric J Horvitz, and Aaron Hoff. 2014. characterizing and predicting postpartum depression from shared facebook data. In Proc. CSCW ’14. ACM, 626–638.

  11. Munmun De Choudhury, Andres Monroy-Hernandez, and Gloria Mark. 2014. “Narco” Emotions: Affect and Desensitization in Social Media during the Mexican Drug War. In Proc. CHI ’14. ACM.

  12. Satarupa Guha, Tanmoy Chakraborty, Samik Datta, Mohit Kumar, Vasudeva Varma. TweetGrep: Weakly Supervised Joint Retrieval and Sentiment Analysis of Topical Tweets. In the proceedings of ICWSM 2016.

  13. Soroush Vosoughi, Deb Roy. A Semi-Automatic Method for Efficient Detection of Stories on Social Media. In the proceedings of ICWSM 2016.

  14. David Alvarez-Melis, Martin Saveski. Topic Modeling in Twitter: Aggregating Tweets by Conversations. In the proceedings of ICWSM 2016.

  15. Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky. How to Ask for a Favor: A Case Study on the Success of Altruistic Requests. In the proceedings of ICWSM 2014.

  16. Efthymios Kouloumpis, Theresa Wilson & Johanna Moore 2011. Twitter Sentiment Analysis: The Good the Bad and the OMG! (ICWSM ’11)

  17. Alexander Pak and Patrick Paroubek 2010. Twitter as a Corpus for Sentiment Analysis and Opinion Mining. In LREC, vol. 10, pp. 1320-1326.

  18. Aliaksei Severyn, and Alessandro Moschitti. Twitter sentiment analysis with deep convolutional neural networks. Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2015.

  19. Cícero Nogueira dos Santos, and Maira Gatti. Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts. COLING. 2014.

  20. Duyu Tang, Furu Wei, Nan Yang, Ming Zhou, Ting Liu, and Bing Qin. Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification. In ACL (1), pp. 1555-1565. 2014.

  21. 1. Vaziripour, Elham, Christophe Giraud-Carrier, and Daniel Zappala. Analyzing the Political Sentiment of Tweets in Farsi. Tenth International AAAI Conference on Web and Social Media. 2016.

  22. 2. Peng, Nanyun, Yiming Wang, and Mark Dredze. Learning Polylingual Topic Models from Code-Switched Social Media Documents. ACL (2). 2014.

  23. 3. Weerkamp, Wouter, Simon Carter, and Manos Tsagkias. How people use twitter in different languages. (2011): 1-2.

  24. 4. Volkova, Svitlana, Theresa Wilson, and David Yarowsky. Exploring Demographic Language Variations to Improve Multilingual Sentiment Analysis in Social Media. EMNLP. 2013.

  25. Anupam Jamatia, Bjorn Gambäck, and Amitava Das.  2015. Part-of-Speech Tagging for Code-Mixed English-Hindi Twitter and Facebook Chat Messages. Proceedings of Recent Advances in Natural Language Processing, page 239.

  26. Sujan Kumar Saha, Partha Sarathi Ghosh, Sudeshna Sarkar, and Pabitra Mitra. 2008. Named Entity Recognition in Hindi using Maximum Entropy and Transliteration. Research journal on Computer Science and Computer Engineering with Applications, pp. 33–41.

  27. Ayush Kumar, Sarah Kohail, Asif Ekbal, and Chris Biemann. 2015. IIT-TUDA: System for sentiment analysis in indian languages using lexical acquisition. Mining Intelligence and Knowledge Exploration, pages 684–693.

  28. Gupta, A., Lamba, H., Kumaraguru, P., and Joshi, A. Faking Sandy: Characterizing and Identifying Fake Images on Twitter during Hurricane Sandy. 2nd International Workshop on Privacy and Security in Online Social Media (PSOSM), in conjunction with the 22th International World Wide Web Conference (WWW) (2013).

  29. Gupta, A., Lamba, H., and Kumaraguru, P. $1.00 per RT #BostonMarathon #PrayForBoston: Analyzing Fake Content on Twitter. IEEE APWG eCrime Research Summit (eCRS), 2013.

  30. https://www.facebook.com/americanmuslims1/photos/a.809524959106862.1073741828.527806667278694/990645217661501/?type=1&theater

  31. https://github.com/tesseract-ocr/tesseract

  32. https://developers.facebook.com/docs/graph-api/reference/v2.7/post#read

  33. https://www.facebook.com/ChristianChronicle/photos/a.83579936833.99565.11127431833/10153806013491834/?type=3&theater

  34. https://www.facebook.com/roberta.metsola/photos/a.406836966100205.1073741826.406824526101449/839065439544020/?type=3&theater

  35. https://www.facebook.com/516601545154233/photos/a.519535361527518.1073741828.516601545154233/574613042686416/?type=3&theater