arXiv subjects

Saptarshi Ghosh

Publications and source records attributed to Saptarshi Ghosh.

106 records · Page 6Linked to original sources

arXiv2017

Is repulsion good for the health of Chimeras?

Yes! Very much so. A chimera state refers to the coexistence of a coherent-incoherent dynamical evolution of identically coupled oscillators. We investigate the impact of multiplexing of a lyer having repulsively coupled oscillators on occurrence of chimeras in the layer having attractively coupled identical oscillators. We report that there exists an enhancement in the appearance of chimera state in one layer of multiplex network in the presence of repulsive coupling in the other layer. Furthermore, we show that a small amount of inhibition or repulsive coupling in one layer is sufficient to yield chimera state in another layer by destroying its synchronized behavior. These results can be used to get insight into dynamical behaviors of those systems where both attractive and repulsive coupling exist among their constituents.

nlin.CD↗

arXiv2017

On Quantifying Knowledge Segregation in Society

With rapid increase in online information consumption, especially via social media sites, there have been concerns on whether people are getting selective exposure to a biased subset of the information space, where a user is receiving more of what she already knows, and thereby potentially getting trapped in echo chambers or filter bubbles. Even though such concerns are being debated for some time, it is not clear how to quantify such echo chamber effect. In this position paper, we introduce Information Segregation (or Informational Segregation) measures, which follow the long lines of work on residential segregation. We believe that information segregation nicely captures the notion of exposure to different information by different population in a society, and would help in quantifying the extent of social media sites offering selective (or diverse) information to their users.

cs.SI↗

arXiv2017

Microblog Retrieval for Post-Disaster Relief: Applying and Comparing Neural IR Models

Microblogging sites like Twitter and Weibo have emerged as important sourcesof real-time information on ongoing events, including socio-political events, emergency events, and so on. For instance, during emergency events (such as earthquakes, floods, terror attacks), microblogging sites are very useful for gathering situational information in real-time. During such an event, typically only a small fraction of the microblogs (tweets) posted are relevant to the information need. Hence, it is necessary to design effective methodologies for microblog retrieval, so that the relevant tweets can be automatically extracted from large sets of documents (tweets). In this work, we apply and compare various neural network-based IR models for microblog retrieval for a specific application, as follows. In a disaster situation, one of the primary and practical challenges in coordinating the post-disaster relief operations is to know about what resources are needed and what resources are available in the disaster-affected area. Thus, in this study, we focus on extracting these two specific types of microblogs or tweets namely need tweets and avail tweets, which are tweets which define some needs of the people and the tweets which offer some solutions or aid for the people, respectively.

cs.IR↗

arXiv2017

Characterizing Information Diets of Social Media Users

With the widespread adoption of social media sites like Twitter and Facebook, there has been a shift in the way information is produced and consumed. Earlier, the only producers of information were traditional news organizations, which broadcast the same carefully-edited information to all consumers over mass media channels. Whereas, now, in online social media, any user can be a producer of information, and every user selects which other users she connects to, thereby choosing the information she consumes. Moreover, the personalized recommendations that most social media sites provide also contribute towards the information consumed by individual users. In this work, we define a concept of information diet -- which is the topical distribution of a given set of information items (e.g., tweets) -- to characterize the information produced and consumed by various types of users in the popular Twitter social media. At a high level, we find that (i) popular users mostly produce very specialized diets focusing on only a few topics; in fact, news organizations (e.g., NYTimes) produce much more focused diets on social media as compared to their mass media diets, (ii) most users' consumption diets are primarily focused towards one or two topics of their interest, and (iii) the personalized recommendations provided by Twitter help to mitigate some of the topical imbalances in the users' consumption diets, by adding information on diverse topics apart from the users' primary topics of interest.

cs.SI↗

arXiv2017

Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media

Search systems in online social media sites are frequently used to find information about ongoing events and people. For topics with multiple competing perspectives, such as political events or political candidates, bias in the top ranked results significantly shapes public opinion. However, bias does not emerge from an algorithm alone. It is important to distinguish between the bias that arises from the data that serves as the input to the ranking system and the bias that arises from the ranking system itself. In this paper, we propose a framework to quantify these distinct biases and apply this framework to politics-related queries on Twitter. We found that both the input data and the ranking system contribute significantly to produce varying amounts of bias in the search results and in different ways. We discuss the consequences of these biases and possible mechanisms to signal this bias in social media search systems' interfaces.

cs.SI↗

arXiv2017

Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations

Users of social media sites like Facebook and Twitter rely on crowdsourced content recommendation systems (e.g., Trending Topics) to retrieve important and useful information. Contents selected for recommendation indirectly give the initial users who promoted (by liking or posting) the content an opportunity to propagate their messages to a wider audience. Hence, it is important to understand the demographics of people who make a content worthy of recommendation, and explore whether they are representative of the media site's overall population. In this work, using extensive data collected from Twitter, we make the first attempt to quantify and explore the demographic biases in the crowdsourced recommendations. Our analysis, focusing on the selection of trending topics, finds that a large fraction of trends are promoted by crowds whose demographics are significantly different from the overall Twitter population. More worryingly, we find that certain demographic groups are systematically under-represented among the promoters of the trending topics. To make the demographic biases in Twitter trends more transparent, we developed and deployed a Web-based service 'Who-Makes-Trends' at twitter-app.mpi-sws.org/who-makes-trends.

cs.SI↗

arXiv2016

Interplay of inhibition and multiplexing : Largest eigenvalue statistics

The largest eigenvalue of a network provides understanding to various dynamical as well as stability properties of the underlying system. We investigate an interplay of inhibition and multiplexing on the largest eigenvalue statistics of networks. Using numerical experiments, we demonstrate that presence of the inhibitory coupling may lead to a very different behaviour of the largest eigenvalue statistics of multiplex networks than those of the isolated networks depending upon network architecture of the individual layer. We demonstrate that there is a transition from the Weibull to the Gumbel or to the Frechet distribution as networks are multiplexed. Furthermore, for denser networks, there is a convergence to the Gumbel distribution as network size increases indicating higher stability of larger systems.

physics.soc-ph↗

arXiv2016

Birth and Death of Chimera: Interplay of Delay and Multiplexing

The chimera state with co-existing coherent-incoherent dynamics has recently attracted a lot of attention due to its wide applicability. We investigate non-locally coupled identical chaotic maps with delayed interactions in the multiplex network framework and find that an interplay of delay and multiplexing brings about an enhanced or suppressed appearance of chimera state depending on the distribution as well as the parity of delay values in the layers. Additionally, we report a layer chimera state with an existence of one layer displaying coherent and another layer demonstrating incoherent dynamical evolution. The rich variety of dynamical behavior demonstrated here can be used to gain further insight into the real-world networks which inherently possess such multi-layer architecture with delayed interactions.

nlin.CD↗

arXiv2016

Structural and electronic phase evolution of Tin dioxide

We investigate the effect of controlled annealing on the structural and electronic phase evolution of Tin dioxide from Tin (II) oxyhydroxide prepared by simple precipitation method. Thermogravimetric analysis suggests a complex weight loss-gain process involved, passing through an intermediate phase of tin oxide nanoparticles. The probable structural and electronic phase evolution is discussed using detailed X-ray diffraction and X-ray photoelectron spectroscopy investigations.

cond-mat.mtrl-sci↗

arXiv2016

Synchronization in Delayed Multiplex Networks

We study impact of multiplexing on the global phase synchronizability of different layers in the delayed coupled multiplex networks. We find that at strong couplings, the multiplexing induces the global synchronization in sparse networks. The introduction of global synchrony depends on the connection density of the layers being multiplexed, which further depends on the underlying network architecture. Moreover, multiplexing may lead to a transition from a quasi-periodic or chaotic evolution to a periodic evolution. For the periodic case, the multiplexing may lead to a change in the period of the dynamical evolution. Additionally, delay in the couplings may bring upon synchrony to those multiplex networks which do not exhibit synchronization for the undelayed evolution. Using a simple example of two globally connected layers forming a multiplex network, we show how delay brings upon a possibility for the inter layer global synchrony, that is not possible for the undelayed evolution.

nlin.CD↗

arXiv2016

Emergence of chimera in multiplex network

Chimera is a relatively new emerging phenomenon where coexistence of synchronous and asynchronous state is observed in symmetrically coupled dynamical units. We report observation of the chimera state in multiplex networks where individual layer is represented by 1-d lattice with non-local interactions. While, multiplexing does not change the type of the chimera state and retains the multi-chimera state displayed by the isolated networks, it changes the regions of the incoherence. We investigate emergence of coherent-incoherent bifurcation upon varying the control parameters, namely, the coupling strength and the network size. Additionally, we investigate the effect of initial condition on the dynamics of the chimera state. Using a measure based on the differences between the neighboring nodes which distinguishes smooth and non-smooth spatial profile, we find the critical coupling strength for the transition to the chimera state. Observing chimera in a multiplex network with one to one inter layer coupling is important to gain insight to many real world complex systems which inherently posses multilayer architecture.

nlin.CD↗

arXiv2014

Reverse Engineering Socialbot Infiltration Strategies in Twitter

Data extracted from social networks like Twitter are increasingly being used to build applications and services that mine and summarize public reactions to events, such as traffic monitoring platforms, identification of epidemic outbreaks, and public perception about people and brands. However, such services are vulnerable to attacks from socialbots $-$ automated accounts that mimic real users $-$ seeking to tamper statistics by posting messages generated automatically and interacting with legitimate users. Potentially, if created in large scale, socialbots could be used to bias or even invalidate many existing services, by infiltrating the social networks and acquiring trust of other users with time. This study aims at understanding infiltration strategies of socialbots in the Twitter microblogging platform. To this end, we create 120 socialbot accounts with different characteristics and strategies (e.g., gender specified in the profile, how active they are, the method used to generate their tweets, and the group of users they interact with), and investigate the extent to which these bots are able to infiltrate the Twitter social network. Our results show that even socialbots employing simple automated mechanisms are able to successfully infiltrate the network. Additionally, using a $2^k$ factorial design, we quantify infiltration effectiveness of different bot strategies. Our analysis unveils findings that are key for the design of detection and counter measurements approaches.

cs.SI↗

arXiv2007

Fermionic representation for the ferromagnetic Kondo lattice model -- diagrammatic study of spin-charge coupling effects on magnon excitations

A purely fermionic representation is introduced for the ferromagnetic Kondo lattice model which allows conventional diagrammatic tools to be employed to study correlation effects. Quantum 1/S corrections to magnon excitations are investigated using a systematic inverse-degeneracy expansion scheme which incorporates correlation effects in the form of self-energy and vertex corrections, while explicitly preserving the continuous spin-rotation symmetry. Magnon self-energy is studied in the full range of interaction strength, and shown to result in strong magnon damping and anomalous softening for zone boundary modes, which accounts for several zone-boundary anomalies observed in recent spin-wave measurements of ferromagnetic manganites.

cond-mat.str-el↗

arXiv2007

Correlation effects on magnetic frustration in the triangular-lattice Hubbard model

Evolution of the magnetic response function in the triangular-lattice Hubbard model is studied with interaction strength within a systematic inverse-degeneracy expansion scheme which incorporates self-energy and vertex corrections and explicitly preserves the spin-rotation symmetry. It is shown that at half filling the response function goes through a nearly dispersionless regime around K for intermediate coupling strength, before undergoing an inversion at strong coupling, resulting in maximum response at the K point, consistent with the expected 120^o AF instability. Effects of finite hole/electron doping on the magnetic response function are also examined.

cond-mat.str-el↗

arXiv2007

High energy kink in the dispersion of a hole in an antiferromagnet -- double-occupancy effects on electronic excitations

Evolution of the hole spectral function along the Gamma-(pi,pi) cut is studied in the antiferromagnetic state of the Hubbard model. The kink in the calculated hole dispersion, the sharp spectral-weight transfer between the branches, and the drastically suppressed coherent spectral weight near k=(0,0), as observed recently in the high-resolution ARPES studies of cuprate antiferromagnets, are shown to be strongly enhanced by finite-U double-occupancy effects. Together with the anomalous spin-wave dispersion observed earlier in high-resolution neutron-scattering studies, the present study provides further evidence of a unified description of magnetic and electronic excitations in cuprate antiferromagnets in terms of the Hubbard model.

cond-mat.str-el↗

arXiv2006

Anisotropic Hubbard model on a triangular lattice -- spin dynamics in Ho Mn O_3

The recent neutron-scattering data for spin-wave dispersion in $\rm Ho Mn O_3$ are well described by an anisotropic Hubbard model on a triangular lattice with a planar (XY) spin anisotropy. Best fit indicates that magnetic excitations in $\rm Ho Mn O_3$ correspond to the strong-coupling limit $U/t > \sim 15$, with planar exchange energy $J=4t^2/U \simeq 2.5$meV and planar anisotropy $ΔU \simeq 0.35$meV.

cond-mat.str-el↗