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Khaki on Screen: Understanding the Representation of Cops in Malayalam Cinema
[No abstract available] -
Memes as multimodal ensemble
Memes have now become a common medium of communication. There are multiple ways memes are considered in academia. Semiotics offers information on how the media and modes that memes consist of can be interpreted and how the characteristics of semiotic resources apply to memes. Drawing from a pool of memes collected during the Kerala assembly election in 2021, this research argues that certain memes need to be categorised as multimodal ensemble. Different modalities play different roles meaning construction, and they also collaborate with each other for a uniform purpose. By comparing existing memes defined in academia and multiple methodologies to analyse memes, the paper puts forth a framework to analyse memes. 2023 De Gruyter Mouton. All rights reserved. -
Khaki on Screen: Understanding the Representation of Cops in Malayalam Cinema
[No abstract available] -
Memes as ensemble of illocutionary acts
As digital communication continues to shape discourse, memes have emerged as a potent tool for conveying messages. Previous studies on internet memes have focused on various aspects such as humor generation, speech acts, and political communication. Although there are studies on speech acts and memes, research specifically examining speech acts within subcultures is scarce. This paper aims to fill that gap by examining the illocutionary acts in political memes within a subculture. To understand how illocutionary acts function in memes, 50 political memes that appeared during the Kerala state assembly election were analyzed using the framework of speech acts. The analysis revealed that memes often contain multiple illocutionary acts. Additionally, it was observed that a single meme can encompass several illocutionary acts simultaneously. This study highlights the complexity and richness of political memes as a form of communication within subcultures, demonstrating how they can convey layered and multifaceted messages through the use of illocutionary acts. 2025 the author(s), -
Ranjith cinemas - An episteme that create discourse on class, caste and religion /
Films are an important form of mass communication in India today. Apart from being mode of entertainment, films also shape the ideology in the mind of viewers because cinema is an ideological apparatus by nature of its very seamlessness. The audience do not see how the cinema creates ideology it invisibly renders and naturalizes it. -
Stirling number of the fourth kind and Lucky partitions of a finite set
The concept of Lucky k-polynomials and in particular Lucky ?polynomials was recently introduced. This paper introduces Stirling number of the fourth kind and Lucky partitions of a finite set in order to determine either the Lucky k- or Lucky ?-polynomial of a graph. The integer partitions influence Stirling partitions of the second kind. 2021 Azarbaijan Shahid Madani University. -
A note on perfect lucky k-colourable graphs
This paper presents the notion of perfect Lucky k-colouring. Basic conditions for a perfect Lucky k-colourable graph are presented. Application thereof is then presented by obtaining the Lucky 4-polynomials for all connected graphs G on six vertices with ten edges. The chromatic number of these connected graphs is ?(G) = 3 or 4. For k = max{?(G): 3 or 4g = 4, it is possible to find Lucky 4-polynomials for all graphs on six vertices and ten edges. The methodology improves substantially on the fundamental methodology such that, vertex partitions begin with Lucky partition forms immediately. Finally, further problems for research related to this study are presented. 2020, International Scientific Research Publications. All rights reserved. -
Chromatic completion number
The well known concept of proper vertex colouring of a graph is used to introduce the construction of a chromatic completion graph and determining its related parameter, the chromatic completion number of a graph. The chromatic completion numbers of certain classes of cycle derivative graphs and helm graphs are then presented. Finally, we discuss further problems for research related to this concept. 2020 the author(s). -
Tattooing and the Tattoo Number of Graphs
Consider a network D of pipes which have to be cleaned using some cleaning agents, called brushes, assigned to some vertices. The minimum number of brushes required for cleaning the network D is called its brush number. The tattooing of a simple connected directed graph D is a particular type of the cleaning in which an arc are coloured by the colour of the colour-brush transiting it and the tattoo number of D is a corresponding derivative of brush numbers in it. Tattooing along an out-arc of a vertex v may proceed if a minimum set of colour-brushes is allocated (primary colours) or combined with those which have arrived (including colour blends) together with mutation of permissible new colour blends, has cardinality greater than or equal to dG+v. 2020 World Scientific Publishing Company. -
Some new results on proper colouring of edge-set graphs
In this paper, we present a foundation study for proper colouring of edge-set graphs. The authors consider that a detailed study of the colouring of edge-set graphs corresponding to the family of paths is best suitable for such foundation study. The main result is deriving the chromatic number of the edge-set graph of a path, Pn+1, n ? 1. It is also shown that edge-set graphs for paths are perfect graphs. 2020 the author(s). -
On the rainbow neighbourhood number of set-graphs
In this paper, we present results for the rainbow neighbourhood numbers of set-graphs. It is also shown that set-graphs are perfect graphs. The intuitive colouring dilemma in respect of the rainbow neighbourhood convention is clarified as well. Finally, the new notion of the maximax independence, maximum proper colouring of a graph and a new graph parameter called the i-max number of G are introduced as a new research direction. 2020 the author(s). -
Rainbow neighbourhood number of graphs
In this paper, we introduce the notion of the rainbow neighbourhood and a related graph parameter namely the rainbow neighbourhood number and report on preliminary results thereof. The closed neighbourhood N [v] of a vertex v ? V (G) which contains at least one coloured vertex of each colour in the chromatic colouring of a graph is called a rainbow neighbourhood. The number of rainbow neighbourhoods in a graph G is called the rainbow neighbourhood number of G, denoted by r?(G). We also introduce the concepts of an expanded line graph of a graph G and a v-clique of v ? V (G). With the help of these new concepts, we also establish a necessary and sufficient condition for the existence of a rainbow neighbourhood in the line graph of a graph G. 2019 Johan Kokand Sudev Naduvath and Muhammad Kamran Jamil. -
Generalisation of the rainbow neighbourhood number and k-jump colouring of a graph
In this paper, the notions of rainbow neighbourhood and rainbow neigh-bourhood number of a graph are generalised and further to these general-isations, the notion of a proper k-jump colouring of a graph is also intro-duced. The generalisations follow from the understanding that a closed k-neighbourhood of a vertex v ? V (G) denoted, Nk [v] is the set, Nk [v] = {u: d(v, u) ? k, k ? N and k ? diam(G)}. If the closed k-neighbourhood Nk [v] contains at least one of each colour of the chromatic colour set, we say that v yields a k-rainbow neighbourhood. 2020, Eszterhazy Karoly College. All rights reserved. -
A Study on Ornated Graphs
In this paper, we introduce the notion of a finite non-simple directed graph called, an ornated graph. An ornated graph is a directed graph on n vertices, denoted by On(sl), whose vertices are consecutively labeled clockwise on the circumference of a circle and constructed from an ordered string sl. Joining vertices is such that for an odd indexed entry at of the string, a tail vertex vi has clockwise heads vj if and only if (i + at) ? j. For an even indexed entry as of the string, a tail vertex vi has anticlockwise heads vj if and only if (i - as) ? j. Some interesting results for certain types of ornated graphs are presented. 2023 World Scientific Publishing Company. -
Root cause analysis of COVID-19 cases by enhanced text mining process
The main focus of this research is to find the reasons behind the fresh cases of COVID-19 from the publics perception for data specific to India. The analysis is done using machine learning approaches and validating the inferences with medical professionals. The data processing and analysis is accomplished in three steps. First, the dimensionality of the vector space model (VSM) is reduced with improvised feature engineering (FE) process by using a weighted term frequency-inverse document frequency (TF-IDF) and forward scan trigrams (FST) followed by removal of weak features using feature hashing technique. In the second step, an enhanced K-means clustering algorithm is used for grouping, based on the public posts from Twitter. In the last step, latent dirichlet allocation (LDA) is applied for discovering the trigram topics relevant to the reasons behind the increase of fresh COVID-19 cases. The enhanced K-means clustering improved Dunn index value by 18.11% when compared with the traditional K-means method. By incorporating improvised two-step FE process, LDA model improved by 14% in terms of coherence score and by 19% and 15% when compared with latent semantic analysis (LSA) and hierarchical dirichlet process (HDP) respectively thereby resulting in 14 root causes for spike in the disease. 2022 Institute of Advanced Engineering and Science. All rights reserved. -
A two-stepped feature engineering process for topic modeling using batchwise LDA with stochastic variational inference model
Online ratings and customer feedback on hotel booking websites support the decision-making process of the customer as the reviews provide a deeper understanding about all aspects of a hotel. Consequently, review and rating analyses are of great interest to consumers and hotel owners for the hotel related social media services. The key challenge, however, is to make the wide variety of information accessible in a simple, fast and relevant way and the solution is Topic Modelling and Opinion Mining. Common approaches like Latent Semantic Analysis (LSA) and Hierarchical Dirichlet Process (HDP) have order affects. If the input dataset is shuffled then different topics are generated leading to misleading results. To overcome this, a two-stepped feature engineering process is used: first step is to use a TF-IDF with modified trigrams calculation followed by the second step in removing weak features from the corpus thereby reducing the dimensionality of the Vector Space Model (SVM) for efficient Topic Modeling and sentiment analysis of the considered corpus. Sentiment score is calculated using VADER tool and Topic Modeling is done with Batch Wise Latent Dirichlet Allocation (LDA) using Stochastic Variational Inference (SVI) model. The modified trigrams included calculation of probabilities of words not only in the backward direction but also the probability calculation of the next two words of the target word thereby retaining its context information. The proposed method using Batchwise LDA with SVI along with two-stepped feature engineering process considerably improved its performance when compared to LSA and HDP models due to the fact of identifying hidden and relevant topics in terms of their optimized posterior distribution in hotel reviews dataset. The Batchwise LDA with SVI improved its performance by 3% in terms of its coherence values by using two-stepped feature engineering process and by 9% and 4% increase when compared with LSA and HDP models respectively. 2020, Intelligent Network and Systems Society. -
Identification of misconceptions about corona outbreak using trigrams and weighted TF-IDF model
Misconceptions of a particular issue like health, diseases, politics, government policies, epidemics and pandemics have been a social issue for a number of years, particularly after the advent of social media, and often spread faster than true truth. The engagement with social media like Twitter being one of the most prominent news outlets continuing is a major source of information today, particularly the information distributed around the network. In this paper, the efficacy of Misconception Detection System was tested on Corona Pandemic Dataset extracted from Twitter posts. A Trigram and a weighted TF-IDF Model followed by a supervised classifier were used for categorizing the dataset into two classes: one with misconceptions about COVID-19 virus and the other comprising correct and authenticated information. Trigrams were more reliable as the functional words related to coronavirus appeared more frequently in the corpus created. The proposed system using a combination of trigrams and weighted TF-IDF gave relevant and a normalized score leading to an efficient creation of vector space model and this has yielded good performance results when compared with traditional approaches using Bag of Words and Count Vectorizer technique where the vector space model was created only through word count. 2020, Institute of Advanced Scientific Research, Inc. All rights reserved. -
Self-supervised learning based anomaly detection in online social media
Online Social Media (OSM) produce enormous data related to the human behaviours based on their interactions. One such data is the opinions expressed and posted for any specific issue addressed in the OSM. Majority of the opinions posted would be categorized as positive, negative and neutral. The lighter group's opinions are termed anomalous as it is not conforming the regular opinions posted by other users. Though, lot of conventional classification and clustering based learning algorithms works well under supervised and un-supervised environment, due to the inherent ambiguity in the tweeted data, anomaly detection poses a bigger challenge in text mining. Though the data is un-supervised, for the learning purpose it is treated as Supervised Learning by assigning class labels for the training data. This paper attempts to give an insight into various anomalies of OSM and identify behavioural anomalies for a Twitter Dataset on user's opinions on demonetization policy in India. Through Self-Supervised learning, it is observed that 86% of the user's opinions did agree to the demonetization policy and the remaining have posted negative opinions for the policy implemented. 2020, Intelligent Network and Systems Society. -
A comparative study of text mining algorithms for anomaly detection in online social networks
Text mining is a process by which information and patterns are extracted from textual data. Online Social Networks, which have attracted immense attention in recent years, produces enormous text data related to the human behaviours based on their interactions with each other. This data is intrinsically unstructured and ambiguous in nature. The data involves incorrect spellings and inaccurate grammars leading to lexical, syntactic and semantic ambiguities. This causes wrong analysis and inappropriate pattern identification. Various Text Mining approaches are being used by researchers which can help in Anomaly Detection through Topic Modeling, identification of Trending Topics, Hate Speeches and evolution of the communities in Online Social Networks. In this paper, a comparative analysis of the performance of four classification algorithms, Support Vector Machine (SVM), Rocchio, Decision Trees and K-Nearest Neighbour (KNN) for a Twitter data set is presented. The experimental study revealed that SVM outperforms better than other classifiers, and also classifies the dataset into anomalous and non-anomalous users opinions. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.