Faculty Publications

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    An iterative MapReduce framework for sports-based tweet clustering
    (Association for Computing Machinery acmhelp@acm.org, 2015) Saxena, G.; Santurkar, S.
    In recent years, social media has evolved into a vital source for real-time information. Sports is one of the most popular topics on social media and attracts the attention of users all over the world. However, a large amount of data is generated on a daily basis, making it difficult for the fans to follow the topics of their interest. Clustering of these posts can resolve this issue by retrieving unambiguous and distinct topics. MapReduce is a programming paradigm that is very effective in designing distributed applications that can be deployed on the cloud. Clustering algorithms are generally iterative in nature. The performance gain offered by MapReduce cannot be completely realized by these algorithms due to the inherent architectural bottlenecks associated with iterative tasks. Twister is a MapReduce-based framework designed to minimize these bottlenecks. In this paper, we propose a distributed framework that gathers sports-related tweets and clusters them into distinct topics using the DB-SCAN algorithm customized for Twister. The accuracy of the framework was analysed using the precision-recall scoring mechanism to determine the set of DBSCAN and framework parameters that result in the best set of clusters. The performance of our framework is evaluated based on our clustering results and simulations using the MRSim simulator. We expect that this framework could be used as a model for performing topic detection over generic tweets. We have used the domain of sports to establish the proof of this concept. © 2015 ACM.
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    Trigger Event and Hate Content: Insights from Twitter Analytics
    (Institute of Electrical and Electronics Engineers Inc., 2019) Chetty, N.; Alathur, S.
    The problematic act damages the target and seeds the fear in the neighborhood. Social media sites are used for planning and coordinating problematic acts. The problematic act is a trigger event which influences hatred feeling. The objective of the paper is to analyze the aftermath of a recent problematic incident in the southern part of the Asian continent from Twitter content. After the problematic incident, citizens used to share their views over social media sites. A total of 48,819 opinions shared through Twitter social media are collected and analyzed using the software developed in the R programming language. The results show hatred against the problematic act through different related emotions. Results also contain more negative tweets which are almost thrice the positive tweets. Fear and anger emotions exhibit a high degree of emotions than the other. © 2019 IEEE.
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    Policies to Mitigate Select Consequence of Social Media: Insights from India
    (Springer, 2020) Chetty, N.; Alathur, S.
    Apart from the benefits to humanity, often, social media possess consequences such as online hate content, fake news, online abuse, cyber-bullying and other demeaning expressions. As the increased hate content causes several health issues, it is necessary to mitigate it. Hate content mitigation may attain sustainable development goals of United Nations. Therefore, the objective of the article is to identify the possible policies to mitigate social media consequence-online hate content. In this regard, online and offline opinions from the Indian respondents are gathered through the questionnaire designed for the purpose. The software which is developed in R programming language is used to analyse opinions. The analysis results reveal the role of government and non-government authorities for digital hate content reduction. The non-governmental communities-civil societies, private sectors, and intermediaries are more important to reduce digital hate content. © 2020, Springer Nature Singapore Pte Ltd.
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    Health Fear Mongering Make People More Sicker: Twitter Analysis in the Context of Corona Virus Infection
    (Springer Science and Business Media Deutschland GmbH, 2020) Jayan, J.; Alathur, S.
    The purpose of this study is to assess the fear factor in Social media data in the context of Coronavirus Disease - 2019(COVID-19) across the globe. The fear generated from social media content will adversely affect the mental health of the public. Design/methodology/approach: The study is followed by a literature survey during the emergence of social media and Internet technologies since the year 2006 where the people commonly started to use the internet across the world. The Twitter data collected on COVID-19 during the infection period and the analysis. Findings: The social media contents adversely affect the mental health of the common public and also the healthcare programs run by the government organizations to some extent. The findings show that the social media are the major source of fear-mongering information and the people behind the fear-mongering are making use of the disaster situation to set their agenda. The strict enactment of law and the efforts by the social media platforms can reduce the fake news and misinformation. Research limitations/implications: The research focuses only on the Twitter data for the analysis during the COVID-19 distress. The detailed study needs to be done in similar distress situations across the globe. The data retrieval became limited from different social media platforms because of privacy issues. © 2020, IFIP International Federation for Information Processing.
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    Developing Indian Smart Cities: Insights from Social Media
    (Springer Science and Business Media Deutschland GmbH, 2020) Chetty, N.; Alathur, S.
    Smart cities play an important role in overall development of a nation by progressing with economic, environmental and social domains. India has projected to create 100 smart cities in near future. The purpose of the paper is to identify the key influencing components and the social media users’ expectations for smart cities development in India. The Twitter social media content of smart cities council and the user posts on smart cities are collected through Twitter application programming interface. The collected tweets are cleaned by pre-processing methods and analyzed for insights. Technology, infrastructure, innovation, transport, mobility and management are the key influencing components for smart cities development in India. The social media users are expecting to emphasize on combating the issues like Covid-19 and use of IoT technology for the success of smart cities project. The integration of different components could increase the success of the project. The analysis of the content shared by the groups (smart cities council and the social media users) which are at different sides of smart cities’ development project, increases the novelty of the study. © 2020, IFIP International Federation for Information Processing.
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    2019-nCoV disease control and rehabilitation: Insights from twitter analytics
    (Institute of Electrical and Electronics Engineers Inc., 2020) Chetty, N.; Alathur, S.; Kumar, V.
    Coronaviruses are the large family of viruses and life threatening with the capabilities to cause respiratory related diseases. The current outbreak of 2019-nCoV (novel Coronavirus) is challenging governance authorities and health care systems around the globe. The epidemic of 2019-nCoV is affecting people globally. The purpose of this paper is to examine the current status of disease control and rehabilitation in relation to outbreak of 2019-nCoV. In this regard, the Twitter social media contents are collected, analyzed and interpreted. Using a set of appropriate keywords, 110000 tweets are extracted from Twitter social media. The collected tweets are first pre-processed and then analyzed with a software developed in R language. The discussions on social media in relation to the outbreak of 2019-nCoV involves disease control, rehabilitation and anti-rehabilitation. Expressions involving specific locations revealed that the discussions are more oriented towards antirehabilitation than rehabilitation and disease control. The content analysis also revealed that the outbreak epidemic victimizes those who possess weaker immune system. © 2020 IEEE.
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    Child online safety in indian context
    (Institute of Electrical and Electronics Engineers Inc., 2020) Andrews, D.; Alathur, S.; Chetty, N.; Kumar, V.
    Children initiates the usage of Internet during young age and spend more time online. Apart from the benefits like improved education, entertainment, news and gaming, Internet poses severe threats to the children online. Ensuring online safety is a global challenge. The purpose of this paper is to examine online social media responses and awareness posts on children online safety. In this relation, Twitter social media responses after freeing the accusers of children sexual harassment and Facebook pages of some prominent personalities in India for online safety are analyzed. The results reveal that though the people are angry and fearful, they believe judiciary and police system and expecting safety from the same. The analysis of Facebook posts depicts that the concerned authorities are active towards child online safety and providing awareness through their representatives. People demand legal actions against the perpetrators of the crime to punish them. The necessary actions should be taken for cyber-crime awareness information to reach all social media users. © 2020 IEEE.
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    Social Media Enabled Rehabilitation Services: Influence of Covid-19 Metaphors
    (Springer Science and Business Media Deutschland GmbH, 2022) Alathur, S.
    This study analyses the social media discussions on disability during the Covid-19 in the Southern part of India. The purpose is to assess the e-participants’ attitude toward disability problems during their social media participation. Participant observation and focus group discussions with citizens often post in social media disability groups. Existing studies less reported the social media disability discussions in regional language, even though it is vital to explore justice at the grassroots level of disability inclusion. The current findings show that citizens’ ill-conceived understanding of disability challenges during the covid-19 results in an unsupportive social media environment. The extreme and exploitation expressions in regional language groups show the lack of local support from the common public for the disabled during the pandemic. The lack of non-institutional voluntary metaphors emphasizes the need to improve the disability support structures at the regional level. Recommendations to enhance e-participation competency are provided. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Depression Severity Detection from Social Media Posts
    (Springer Science and Business Media Deutschland GmbH, 2024) Recharla, N.; Bolimera, P.; Gupta, Y.; Anand Kumar, M.A.
    Regardless of age, gender, or color, mental health problems affect people all over the world. People feel increasingly at ease sharing their opinions on social networking sites (SNS) practically every day in the present era of communication and technology. Reddit is a social networking site that consists of subreddits, or single-topic communities, that are created, maintained, and frequented by anonymous users. The dataset used in the paper is, eRisk2021 dataset provided for task 3, which is used for depression severity measurement. It consists posts of Reddit users. In this paper, the approach involves finding user depression severity based on their Reddit history with the help of the BDI-II questionnaire, which is discussed. The paper provides three different approaches in finding the users depression severity from their social media data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
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    Honour, hate and violence in social media: Insights from India
    (Inderscience Publishers, 2019) Chetty, N.; Alathur, S.
    Honour-based hate content is predominantly generated from family hate content and may affect humanity. In the Indian context, analysis of multiple resources such as literature, reported articles and social media sites pertinent to honour-based hate content is less. Therefore, the purpose of this paper is to identify and understand the influencing factors and emotions of honour-based hate content. A review of literature, news articles on honour killing and the analysis of Twitter content are made to attain the purpose. In India, factor like marrying a person against family members' ideologies is observed as dominating among other factors of honour-based hate content. It has been also observed that emotions such as anger, fear, disgust and sadness are used to express hate. Possible impacts of honour-based hate content on family and society are discussed. The analysis of emotions about honour and hate content increases novelty of the article. © 2019 Inderscience Enterprises Ltd.