Pulak Malhotra’s research while affiliated with International Institute of Information Technology, Hyderabad and other places

Internet search engines have become an integral part of life, but for pop music, people still rely on textual search engines like Google. We propose Pied Piper, a meta search engine for music. It can search for music lyrics, song metadata and song audio or a combination of any of these as the input query and efficiently return the relevant results.

Internet search engines have become an integral part of life, but for pop music, people still rely on textual search engines like Google. We propose Pied piper, a meta search engine for music. It can search for music lyrics, song metadata and song audio or a combination of any of these as the input query and efficiently return the relevant results.

We analyze the computational complexity of the video game "CELESTE" and prove that solving a generalized level in it is NP-Complete. Further, we also show how, upon introducing a small change in the game mechanics (adding a new game entity), we can make it PSPACE-complete.

Google Play Store's policy forbids the use of incentivized installs, ratings, and reviews to manipulate the placement of apps. However, there still exist apps that incentivize installs for other apps on the platform. To understand how install-incentivizing apps affect their users, we examine their ecosystem through a socio-technical lens and perform a longitudinal mixed-methods analysis of their reviews. We shortlist 60 install-incentivizing apps which collectively account for over 160.5M installs on the Google Play Store. We collect 1,000 most relevant reviews on these apps every day for a period of 52 days. First, our qualitative analysis reveals various types of dark patterns that developers incorporate in install-incentivizing apps to extort services and build market at the expense of their users. Second, we highlight the normative concerns of these dark patterns at both the individual and collective levels, elaborating on their detrimental effects on the price transparency and trust in the market of Google Play Store. Third, we uncover evidence of install-incentivizing apps indulging in review and rating fraud. Building upon our findings, we model apps and reviewers as networks and discover lockstep behaviors in the reviewing patterns that are strong indicators of review fraud. Fourth, we leverage the content information of reviews to find that reviewers who co-review more apps also show greater similarity in the content of their reviews, making them more suspicious. Finally, we conclude with a discussion on how our future work will generate implications for Google Play Store to prevent the exploitation of users while preserving transparency and trust in its market.