Ashoka University is a private university located in Sonipat, Haryana, India, focusing on liberal arts and sciences. It was established in 2014.&nbsp;It is guided by an academic council of academics and scholars from around the world. The council sets the university&#39;s academic standard, advising on matters of curriculum, faculty hiring and research.&nbsp;

Ashoka University offers a full-time 3 (+ 1) year undergraduate programme. The University comprises of&nbsp;2500 plus students, with a mix of both national and international students.&nbsp; &nbsp;

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Ashoka University

Despite the importance of elections in India, the world's largest democracy, data on Indian electoral outcomes has not been easily available for political analysis in the past. This has been due to the problems inherent in assembling any data archive of social and political data spanning many decades. In this paper, we shed some light on these problems and present some solutions in the context of a system we built called LokDhaba. LokDhaba includes the first freely-available, structured and cleaned data archive on Indian electoral outcomes at the national or state level from 1962 onwards. To build this archive, we overcame the challenges of data scraping, parsing, cleaning, consistency checking and integration between multiple sources, with the help of some novel tools. LokDhaba is being used extensively by political scientists, researchers, journalists and others to better understand long-term electoral trends in India. © 2020 ACM.

World University root node

Other Publications

COMPASS 2020 - Proceedings of the 2020 3rd ACM SIGCAS Conference on Computing and Sustainable Societies

LokDhaba: Acquiring, Visualizing and Disseminating Data on Indian Elections

Users of web browsers today swim in a sea of haphazardly organized tabs, bookmarks, searches and downloads. This is because browsers operate at the level of individual web pages, and rarely understand the user’s high-level tasks. We propose to address this problem by compartmentalizing the web browsing experience across different tasks defined by the user. Wedescribe Sailboat, an extension for Google Chrome that explores this idea by making user-defined tasks first-class objects in the browsing experience. In Sailboat, different tasks have their own tabs, history, bookmarks and download folders, while maintaining a unified identity across compartments. Sailboat lets the user create and switch between tasks such as "Philosophy Paper", "Summer Internships", and "Trip to China". Users can encapsulate the browsing related to a task, archive it or share it with others, and come back to it months later. Sailboat also tracks and reflects the analytics of time spent on different tasks to aid productivity. Wedeployed Sailboat with several users, and studied how they engaged with it. Our users report that Sailboat aids organized browsing, reduces distractions, and is easy to get used to.

Compartmentalizing web browsing with Sailboat

Animportant question that arises from autobiographical memory research is whether the variables that influence memory in the laboratory also drive memory for autobiographical episodes in real life. We explored this question within the context of e-mail communications and investigated the variables that influence recall for personally familiar names and temporal information in emails. We designed a Web-based program that analyzed each participant’s year-old sent e-mail archive and applied textual analysis algorithms to identify a set of sentences likely to be memorable. These sentences were then used as the stimuli in a cued recall task. Participants saw two sentences from their sent e-mail as a cue and attempted to recall the name of the e-mail recipient. Participants also rated the vividness of recall for the e-mail conversation and estimated the month in which they had written the e-mail. Linear mixed-effect analyses revealed that recipient name recall accuracy decreased with longer retention intervals and increased with greater frequency of contact with the recipient. Also, with longer retention intervals, participants dated e-mails as being more recent than their actual month. This telescoping error was moderately larger for e-mails with greater sentiment. These findings suggest that memoryfor personallyfamiliarnames and temporalinformation ine-mails closely follows the patterns for autobiographical memory and proper-name recall found in laboratory settings. This study introduces an innovative, Web-based experimental method for studying the cognitive processes related to autobiographical memories using ecologically valid, naturalistic communications.

Behavior Research Methods

Autobiographical recall of personally familiar names and temporal information in e-mails: An automatic analytic approach using e-mail communications

ePADD is free and open-source software that supports the computational analysis of email with potential historical or cultural value. The software incorporates techniques from computer science and computational linguistics, including natural language processing, named entity recognition, and other statistical machine learning-associated processes. These functionalities enable ePADD to promote the appraisal, processing, discovery, and delivery of email held by archival repositories and other cultural memory institutions. In November 2015, Stanford Libraries, with partners University of Illinois Urbana-Champaign, Harvard University, University of California, Irvine, and Metropolitan New York Library Council, received three years of funding from the Institute of Museum and Library Services (IMLS) to advance the formation of a national digital platform by further developing ePADD. Now in year two of the grant, Stanford Libraries and its grant partners have continued to improve the program's scalability, usability, and feature set, while simultaneously taking steps to engage and grow the user community. This article provides background on the need for the ePADD software, identifies how ePADD contributes to the national digital platform, informs on the work completed, highlights the ways in which ePADD is being adopted by the community, and identifies next steps and areas for future project development.

D-Lib Magazine

ePADD: Computational analysis software facilitating screening, browsing, and access for historically and culturally valuable email collections

Archives of letters and documents belonging to individuals provide valuable insights into history. In the digital age, such history is being captured in personal digital archives, especially in the form of email. Archival organizations have recognized the importance of email archives and often collect email when they acquire the papers of eminent donors; however they find it difficult to screen, process and provide access to email for research, due to its sheer volume. We describe the considerations we encountered with the email archives of two prominent individuals in the special collections of Stanford University Libraries. We have designed novel approaches to the challenges of (1) Reconciliation with authority records, (2) Making "finding aids" of the archive available to the general public, without revealing confidential information, and (3) Browsing an email archive when one may not know what exactly to look for. Our solutions have been implemented in a publicly available and open source system called ePADD. As a result, we enable donors and archival organizations to appraise, process and screen large-scale email archives, thereby unlocking the historical value embedded in them.