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Phase 1 #LokSabhaElections2019 Social Media Round-up
Today the first of the seven phases of Lok Sabha Elections 2019 went underway in India; we had 91 constituencies spread across 20 states that went for polling. 14.21 crore Indians are expected to have casted their vote today. We collected Twitter data using 123 hashtags, and collected over 2 lakh tweets from 0300hrs until 1900hrs (stay tuned, we will make these data public soon). The cumulative distribution graph of the Tweets posted over the duration of the data collection with the top 5 hashtags can be seen below. The same graph, but depicting the Tweets posted with the top 5 mentions can be seen below. Further, we share the…
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NaMo Vs RaGa: On Twitter, YouTube, Facebook, Instagram, and LinkedIn
As the nation gears up for the first phase of the parliamentary elections tomorrow, it will be interesting to see in detail the emerging candidates vying for the seat of the Prime Minister seat. Taking forward our empirical analysis of Social Media dialogues around elections, we analyze the two primary candidates, Narendra Modi (NaMo) and Rahul Gandhi (RaGa). In this blog, we have a look at their presence on Twitter, Facebook, YouTube, Instagram, and LinkedIn. Before we get into the analysis of their profiles, we quickly visit the recently released manifestos of each of their parties and share a word cloud of the topics addressed in them. To obtain this…
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Who-Follows-Whom?, #ChaupalOnTwitter, Political Satire Videos
Who-Follows-Whom? Earlier in our ongoing blog series on the forthcoming Indian parliamentary elections we had characterized the following network of verified political handles. Today we share the results of analysing the follower/following patterns of these handles amongst each other. To understand the interactions between the political handles (otherwise parties), we populate a table which shows the ratio of total number of followings of one party to another by the total number of handles of that party. Below is the table with all the counts of followings of each party’s members against another party’s handles, e.g. total number of connections from all AAP accounts following BJP accounts is 912. Next, we…
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The #MainBhiChowkidar Campaign: 30% Verified, 36% non-verified Handles added Chowkidar to their Name
Below is the first occurrence of the #MainBhiChowkidar by @narendramodi The tweet was dated March 15th 0900hrs IST. This hashtag was part of the campaign; we found this hashtag trending in India by 1100hrs. We were interested in studying the different facets of this campaign, in particular, name changes in the user name of the accounts, verified and others. Screen name / handle is restricted to 15 alphanumeric characters (letters A-Z, numbers 0-9) with the exception of underscores and name of the account is restricted to 50 alphanumeric characters, including special characters and emojis. First occurrence of MainBhiChowkidar Of the 1,268 verified handles (we reported 1,252 in our blog post…
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MIME: A Social Network for Meme Enthusiasts. A course project turned into 10,000+ Lines of Code.
Memes have become a predominant means of expression in the Internet culture, they are not only used as a means of entertainment but as an important tool for advertising, spreading propaganda and even political ideologies. However, the creation of memes is limited to a niche community of content creators who are skilled in photo/video editing software. MIME is a platform which empowers people who lack these skills to become a part of the meme conversation. We built a one-stop solution for all meme needs – a maker space where people can create memes, a personalized meme feed, and a space to connect with other meme enthusiasts. Further, we hypothesize that…
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Hardening Deep Neural Networks via Adversarial Model Cascades
Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs. Works on securing neural networks against adversarial examples achieve high empirical robustness on simple datasets such as MNIST. However, these techniques are inadequate when empirically tested on complex data sets such as CIFAR10 and SVHN. Further, existing techniques are designed to target specific attacks and fail to generalize across attacks. We propose Adversarial Model Cascades (AMC) as a way to tackle the above inadequacies. Our approach trains a cascade of models sequentially where each model is optimized to be robust towards a mixture of multiple attacks. Ultimately, it yields a single model which…
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Female Political Handles: Followed by more, Post more, Re-tweet more, and Follow less
We manually annotated the 1,252 verified handles, for various characteristics of the handles, like party affiliation, state / city, and gender. Among the 1,252 handles, we found 865 (69.1%) to be men, 133 (10.6%) to be women, and the rest 254 (20.3%) handles to be associated with parties. This blog is dedicated to analysing men and women handles. Analysis was done with the data as of March 1, 2019. We found female political handles to have more followers than males. On average, females had 368.5K (min: 422, max: 12.2M) followers, while male handles has 347.8K (min: 47, max: 46.2M) followers. With @narendramodi having the maximum followers (46.2M) in male and…
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Verified Political Handles: Party Distribution, Political Status, Gender Diversity, and Network Interactions
Our data collection covers 2,585 Twitter handles which we find have some affiliation to an Indian political party. This list was manually curated and we have been collecting data for these handles from late 2018 through the Twitter API. Among these 2,585 handles, we found 1,252 political handles to be Verified Twitter Handles. It is interesting to see this large number of verified accounts in this elections. When we analysed the Twitter data for 2014 Elections, we found only 71 Verified Indian political handles. We manually annotated these handles for their state representation, party affiliation, Lok Sabha / Rajya Sabha affiliation, and gender (in case of a handle representing an…
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WhatsFarzi: Analyzing Fake / Manipulated content / Misinformation on WhatsApp
As mobile coverage penetrates the most remote areas and data packages become cheaper every day, over 4 billion people across the world today have access to the Internet, of which more than 56% traffic comes from mobile devices. This is especially true in developing countries like India, where more than 430 million Indians out of the total online population of 462 million access the Internet through mobile phones. WhatsApp is the most popular personal messaging service in India, with more than 200 million users, the highest in the world. One of the biggest side effects of WhatsApp’s deep penetration is its misuse as a medium to disseminate misinformation. Last year,…
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The Precog Land
All members of Precog are destined to achieve their dreams. Precog not only helps to actualize our goals but dares us to think beyond what we believe is “possible”. Under the dynamic leadership of Prof. Ponnurangam Kumaraguru (“PK”), the Alumni of Precog have been able to get into the world’s best universities and secure jobs in the most sought after companies. I joined Precog in the Summer of 2016 as an Intern – to explore the field of Security and Privacy. I realized that Precog was much more than working on individual projects rather a community where we brainstormed about fresh research ideas. Every week we used to get together in…