Dr. Akrati Saxena
Research Fellow, Eindhoven University of Technology

IBAE Young Achiever Award 2019, Google WTM Scholar 2017, GHCI18 Scholar, HLF18 Young Researcher, GYSS19 Young Scientist

Research Interest: Complex Networks, Social Network Analysis, Computational Social Science, Linguistic Analysis, CrowdSourcing, Social Media

Reviewer/PC Member: IEEE Transactions on Network Science and Engineering, GeoInformatica, Post-ASONAM Edited Book (2016), International Journal of Modern Physics B, International Journal of Data Science and Analysis (November 2018 - December 2020), Data Science Track @ GHC 2019, Poster Track @ GHC 2019, CSS Summer School on Methods for analyzing and modeling multimedia data 2019, TAPIA Conference 2019, RESPECT 2020, CSoNet 2019, Networks and Education track @ HUSO 2019

In preparation / To be submitted

  • Saxena, Akrati, and S. R. S. Iyengar. Global Rank Estimation in Weighted Networks.
  • Saxena, Akrati, Jaspal Singh Saini, and S. R. S. Iyengar. Social Network Analysis of the Caste-Based Reservation System in India.
  • Saxena, Akrati, Lee Mong Li, and Wynne Hsu. Fake News Mitigation Techniques: A Survey.
  • Saxena, Akrati, Vaibhav Malik, and Varnita Saxena. Gender based Role Analysis on StackExchange Portals.

Under Review

  • Akrati Saxena, Ryan Miller, and Ralucca Gera. A community-guided approach for dark network disruption. (Submitting to MORS Journal)

Journals

  • Ivan Bermudez, Daniel Cleven, Ralucca Gera, Erik T. Kiser, Timothy Newlin, and Akrati Saxena. Twitter Response to Munich July 2016 Attack: Network Analysis of Influence. Frontiers in Big Data Journal, 2019
  • Gupta, Yayati, Akrati Saxena, S. R. S. Iyengar, and Debarati Das. Modeling Memetics Using Edge Diversity. SNAM Journal, 2019
  • Saxena, Akrati, Ralucca Gera, and S. R. S. Iyengar. A Heuristic Approach to Estimate Nodes' Closeness Rank Using the Properties of Real World Networks. SNAM Journal, 2018
  • Saxena, Akrati, Ralucca Gera, and S. R. S. Iyengar. Degree Rank Estimation in Complex Networks. SNAM Journal, 2018

Conferences

  • Saxena, Akrati, Lee Mong Li, Wynne Hsu, Hai Leong Chieu, Lynette Ng, and Loo Nin Teow. Mitigating Misinformation in Online Social Network with Top-k Debunkers and Evolving User Opinions. Maison, WWW 2020
  • Saxena, Akrati, Pratishtha Saxena, Harita Reddy, and Ralucca Gera. A Survey on Studying the Social Networks of Students. HUSO 2019
  • Saxena, Akrati, and S. R. S. Iyengar. K-shell Rank Analysis using Local Information. CSONET 2018
  • Miller, Ryan, Ralucca Gera, Akrati Saxena, and Tanmoy Chakraborty. Discovering and leveraging communities in dark multi-layered networks for network disruption. MaHIN, ASONAM 2018
  • Saxena, Akrati, and S. R. S. Iyengar. “Global Rank Estimation in Complex Networks.” ICDCN 2018
  • Saxena, Akrati, Ralucca Gera, and S. R. S. Iyengar. “Fast Estimation of Closeness Centrality Ranking.” Advances in Social Networks Analysis and Mining (ASONAM) (2017)
  • Saxena, Akrati, Ralucca Gera, and S. R. S. Iyengar. “Observe Locally Rank Globally.” Advances in Social Networks Analysis and Mining (ASONAM) (2017)
  • Gera, Ralucca, Ryan Miller, Miguel Miranda Lopez, Akrati Saxena, and Scott Warnke. "Three is the answer: combining relationships to analyze multilayer terrorist networks." Advances in Social Networks Analysis and Mining (ASONAM) (2017).
  • Adeniji, Oludare, David S. Cohick, Victor G. Castro, Ralucca Gera, and Akrati Saxena. "A Generative Model for the Layers of Terrorist Networks." Advances in Social Networks Analysis and Mining (ASONAM) (2017).
  • Saxena, Akrati, and S. R. S. Iyengar. "Evolving Models for Meso-Scale Structures." Comsnets 2016
  • Saxena, Akrati, Vaibhav Malik, and S. R. S. Iyengar. “Estimating the Degree Centrality Ranking.” Comsnets 2016
  • Saxena, Akrati, Yayati Gupta, Debarati Das, and S. R. S. Iyengar. “Modeling Memetics using Edge Diversity.” Complenet 2016
  • Saxena, Akrati, Yayati Gupta, and S. R. S. Iyengar. “Understanding Spreading Patterns on Social Networks Based on Network Topology.” Asonam 2015

Technical Reports

  • Saxena, Akrati, Jaspal Singh Saini, Yayati Gupta, Aishwarya Parasuram, Neeharika, S.R.S. Iyengar. Social Network Analysis of the Caste-Based Reservation System in India. arXiv preprint arXiv:1512.03184.
  • Saxena, Akrati, Vaibhav Malik, and S. R. S. Iyengar. "Estimating the Degree Centrality Ranking of a Node." arXiv preprint arXiv:1511.05732 (2015).
  • Saxena, Akrati, Vaibhav Malik, and S. R. S. Iyengar. "Rank me thou shalln't Compare me." arXiv preprint arXiv:1511.09050 (2015).
  • Saxena, Akrati, et al. "Modeling Memetics using Edge Diversity." arXiv preprint arXiv:1505.00457 (2015).


  Fake News Mitigation Techniques

Today each online social network hosts millions of user accounts. These social networks provide an easy platform to share the information where most of the information is shared as a microblog. Due to the easy sharing of information, the spread of fake news and rumors has been prevalent. We have seen the impact of spreading of fake news on major events like the US election, Jakarta election, or distorting the reputation of a company. In this project, we focus on proposing the mitigation techniques using network science-based approach. We also reviewed the existing fake news detection and mitigation techniques, and what kind of actions can be taken further to control the fake news spreading.

  Estimate Global Rank of a Node using Local Information

In real-world complex networks, the importance of a node depends on two important parameters: 1. characteristics of the node, and 2. the context of the given application. The current literature contains several centrality measures that have been defined to measure the importance of a node based on the given application requirements. In this project, we aim to propose fast and efficient methods to estimate the global centrality rank of a node without computing the centrality value of all the nodes. These methods are further extended to estimate the rank without having the entire network. The proposed methods are based on the structural behavior of centrality measures, network properties, and sampling techniques. We have proposed methods to estimate the degree, closeness, and k-shell rank of the nodes. My Ph.D. thesis is based on this project.

  Social Network Analysis of the Caste-Based Reservation System in India

Being as old as human civilization, discrimination based on various grounds as race, creed, gender, and caste is prevailing in the world from a long time. To undo the impact of this long-enduring historical discrimination, governments worldwide have adopted various forms of affirmative action; such as positive discrimination, employment equity, and quota system. Locally known as “Reservation” policy, affirmative action in India is one of the world's oldest and most complex affirmative policy. Although being one of the most controversial and frequently debated issues, the reservation system in India lacks a rigorous scientific study and analysis. In this paper, we discuss the dynamics of the reservation system based on the cultural divide among Indian population using social network analysis. The mathematical model, using Erdos-Renyi network, shows that the addition of weak ties between the two components leads to a logarithmic reduction in the social distance. Our experimental simulations establish the claim for the different clans of frequently studied social network models as well as real-world networks. We further show that a small number of links created by the process of reservation are adequate for a society to live in harmony.

  Gender Bias and Affirmative Actions

For the past several decades, gender-based biases have been prevalent in society. The gender ratio bias is also present among the people working in STEM. For the past few decades, several govt, organizations, private institutions, NGOs, etc., have worked extensively to reduce the gender gap in STEM. Still, we are far from reaching an equal gender ratio. In this project, we focus on the analysis and modeling of biases in the communities based on gender, race, etc. and the impact of affirmative actions to remove these biases from society. We work towards modeling of biases, actions for removing them, influence propagation, and the emergence of leaders in such scenarios. Apart from this, we also study gender bias in online learning platforms. How different people acquire different roles for the stability of the ecosystem and how they converge over time. This project opens a wide range of questions that are yet to be explored and answered.

  Compare the Evolving Phenomenon of Real-world Networks

Decision makers use partial information networks to guide their decision, yet when they act, they act in the real network or the ground truth. Therefore, a way of comparing the partial information to ground truth is required. In this project, we aim to propose methods for comparing the evolution process of real-world networks. We introduced a statistical measure that analyzes the network obtained from the partially observed information and ground truth, which of course can be applied to the comparison of any networks. As a first step, in the current research, we restrict ourselves to networks of the same size to introduce such a method, which can be generalized to different size networks. Next, we focus on generalizing the proposed method to compare the network of different sizes.

  Evolving Models for Meso-scale Structures

Real-world scale-free networks possess both the community as well as the core-periphery meso-scale structures that shows the modular and hierarchical organization in the given networks. This project mainly focuses on understanding the evolving phenomenon and coexistence of core-periphery community structures. Based on our observations, we further propose evolving models to generate synthetic weighted and unweighted scale-free networks having both meso-scale structures.

  Analysis of Dark Multilayered Networks

In this project, we present a synthesized analysis of three terrorist networks through the analysis of the multiple layers of these networks. First, we study how these networks have different characteristics than scale-free real-world networks. The main challenges associated with these networks are incompleteness, fuzzy boundaries, and dynamic behavior. We account these characteristics and propose a method to identify knowledge sharing communities (KSC). We also proposed models to generate multilayered synthetic networks having similar properties.

  Coreness Approximation using Local Information

For network scientists, it has always been an interesting problem to identify the influential nodes in a given network. K-shell decomposition method is a widely used method which assigns a shell-index value to each node based on its influential power. K-shell method requires the entire network to compute the shell-index of a node that is infeasible for large-scale real-world dynamic networks. In this project, we focus on estimating the shell-index of a node using local neighborhood information. Next, we use the estimated coreness value to estimate the global coreness rank of a node without having the entire network.

  Modeling Memetics using Edge Diversity

In this project, we study how does a meme spread on the network. We study real-world meme spreading datasets to observe the role of core nodes in making a meme viral. We further study the impact of core-periphery and community structure on the meme spreading. Based on our observations, we proposed a meme spreading model using penta-level classification of edges in the network. The proposed spreading model is verified using Twitter datasets.


Experience:

  • Eindhoven University of Technology

    Research Fellow | March 2020 to Present | Netherlands

  • National University of Singapore

    Postdoctoral Fellow | November 2018 to March 2020 | Singapore

  • Indian Institute of Technology Ropar, India

    Research Scholar | July 2014 to October 2018 | Punjab, India

  • State Bank Of India

    IT Officer (Assistant Manager) | August 2013 to July 2014 | Patiala, Punjab, India

  • Newgen Software Technology Ltd.

    Software Developer | July 2011 to August 2013 | New Delhi, India

  • Tulip Telecom Delhi

    Summer Intern | May 2010 to July 2010 | New Delhi India

Teaching Assistantships:

  • GE103, Introduction to Programming and Data Structures with Dr. Nitin Auluck (Spring Semester, 2018, Indian Institute of Technology Ropar)
  • CSL720, Introduction to Spatial Computing with Dr. Venkata M. Viswanath Gunturi (Autumn Semester, 2018, Indian Institute of Technology Ropar)
  • CSL811, Special Topics in Social computing with Dr. S.R.S. Iyengar (Autumn Semester, 2018, Indian Institute of Technology Ropar)
  • CSL471, Introduction to Probability and Computing with Dr. S.R.S. Iyengar (Spring Semester, 2017, Indian Institute of Technology Ropar)
  • CSL343, Computer Networks with Dr. Junghyun Jun (Autumn Semester, 2017, Indian Institute of Technology Ropar)
  • CSL356, Analysis and Design of Algorithms with Dr. Junghyun Jun (Spring Semester, 2016, Indian Institute of Technology Ropar)
  • CSL343, Computer Networks with Dr. Junghyun Jun (Autumn Semester, 2016, Indian Institute of Technology Ropar)
  • CSL469, Wireless and Mobile Systems with Dr. Junghyun Jun (Spring Semester, 2015, Indian Institute of Technology Ropar)
  • CSL451, Introduction to Database Systems with Dr. Narayanan C. Krishnan (Autumn Semester, 2015, Indian Institute of Technology Ropar)
  • GEL103, Introduction to Computing with Dr. Nitin Auluck (Autumn Semester, 2015, Indian Institute of Technology Ropar)
  • CSL407, Machine Learning with Dr. Narayanan C. Krishnan (Spring Semester, 2014, Indian Institute of Technology Ropar)

Research Internships:

  • May 2015 - July 2015, Project: Community detection in multilayer networks, under Dr. Ralucca Gera, Associate Professor, NPS, California, USA
  • September 2015 - December 2015, Project: Community detection in multilayer networks, under Dr. Ralucca Gera, Associate Professor, NPS, California, USA
  • May 2016 - July 2016, Project: Analysis of multilayered terrorist networks, under Dr. Ralucca Gera, Associate Professor, NPS, California, USA
  • April 2017 - July 2017, Project: Study the properties of dark networks and propose evolution models to generate multilayered dark networks, under Dr. Ralucca Gera, Associate Professor, NPS, California, USA

Presentations and Talks

 "K-shell Rank Analysis using Local Information", at CSoNet, Shanghai, China, December 2018

 "Fast and Efficient Methods to Estimate the Centrality Rank of the Nodes in Complex Networks", at IIT Ropar, India, August 2018

 "Fast and Efficient Methods to Estimate Global Rank of the Nodes using Network Characteristics", at IIT Ropar, India, May 2018

  "Global Rank Estimation in Complex Networks" in ICDCN 2018, IIT BHU, India, January 2018

  "Rank me, thou shalln’t compare me: Rank estimation in complex networks", at IIT Ropar, India, December 2017

  "Estimate Closeness Centrality Rank using its Structural Behavior", at IIT Ropar, India, September 2017

  "Rank me thou shan’t Compare me" at CSE department, IIT Ropar, India, October 2016

  "Evolving Models for Meso-Scale Structures" in Comsnets at Bangalore, India, January 2016.

  "Estimating the Degree Centrality Ranking" in Comsnets at Bangalore, India, January 2016.

  "Evolution of Core-Periphery Structure" in NAG15 international workshop held at IIT Ropar, December 2015 .

  "Evolution of Core-Periphery Structure in Complex networks" in Cynosure at IIT Ropar, November 2015

  "Predict the Degree Centrality Ranking" in Cynosure at IIT Ropar, November 2015

  "Evolving Phenomenon of Core in Real World Networks" at CSE Department IIT Ropar, August 2015

  "Synonymy Networks and Their Structure" at CSE Department IIT Ropar, January 2015

 "Virality Prediction in Online Social Networks: A Novel Approach" in TEQIP-II at PEC Chandigarh , November 2014


Students Mentored 

  Priyanshu Ranjan, B.Tech. project, IIT Ropar, July 2016- May 2017.

  Jagadeesh, B.Tech. project, IIT Ropar, July 2016- May 2017.

  Devendra Pratap Yadav, B.Tech. project, IIT Ropar, Jan 2017- December 2017.

  Pushpendra Tiwari, Summer Intern, IIT Ropar, May 2016-July 2016.

  Jayant Bisht, Summer Intern, IIT Ropar, May 2017-July 2017.

  Harita Reddy, Summer Intern, IIT Ropar, May 2017-July 2017.

  Pratik Chhajer, Summer Intern, IIT Ropar, May 2016-July 2016.

  Meghana Batchu, Summer Intern, IIT Ropar, May 2017-July 2017 .

  Sameer Arora, Summer Intern, IIT Ropar, May 2017-July 2017.

  Harsimran Singh, Summer Intern, IIT Ropar, May 2017-July 2017.

  Vardaan Bajaj, Summer Intern, IIT Ropar, May 2017-July 2017.


Dr. Akrati Saxena
Research Fellow
Department of Mathematics and Computer Science,
Eindhoven University of Technology, Netherlands

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