Design of a Novel Query System for Social Network

Design of a Novel Query System for Social Network

Charu Virmani (Manav Rachna International Institute of Research and Studies, Faridabad, India), Dimple Juneja (NIT, Kurukshetra, Kurukshetra, India) and Anuradha Pillai (YMCA University of Science and technology, Faridabad, India)
Copyright: © 2019 |Pages: 19
DOI: 10.4018/JITR.2019040110

Abstract

User intention and nature of network plays a vital role towards the quality of response received as the result of any user query. Therefore, the need of system understanding the user's intent and network dynamism as well is highly apparent. The proposed query processing and analysing system (QPAS) for social networks is based on extracting user's intent from various social networks using existing NLP techniques. It fetches the information and further employs hybrid ensemble k-means hierarchical agglomerative clustering (HEKHAC) and modified Bitonic sort to improve the responses. The proposed approach offers an edge over other mechanisms as it not only retrieves more user-centric results as compared to traditional way of keyword-based searching but also in timely manner as well. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a noteworthy revolution scoring up to precision and recall respectively.
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1. Introduction

With the emergence of web 2.0 (Tang et al. 2017) resulted into the evolution of online social networks which in turn has become an integral and popular part of the modern Internet whose aim is to share and connect with people. The growth and evolution of social media has been in the world since the late 70s providing services like newsgroups, Internet Messengers (IMs), blogs and chat rooms. Moreover, the “Golden era” of social media started in early 20’s that caught immediate attention of innovation like LiveJournal, encyclopedia, Wikipedia that gave massive popularity among internet users all around the world. However, the huge boom of social media was followed by the emergence of LinkedIn in 2002, MySpace in 2003, Facebook in 2004, and Twitter in 2006 (Malhotra et al. 2012). Since then, it became an ever-demanded medium of communication having a larger user base and giving birth to user generated content which is growing exponentially over the years. It is a diverse and easily accessible platform serving as a source for building communities, sharing events of interest around the world, meeting new acquaintance, getting updates, consume news and discuss various topics.

The social aspect introduced by OSN services caught immediate attention and made them immensely popular among Internet users all around the world in a very short span of time. Today, close to two billion users around the world access to the Web and a large number of users have an account and uses services provided by OSN. For instance, Facebook (728 million), 540 million on Google+, 259 million on LinkedIn, and Twitter (320 million) lead the way in terms of the number of monthly active users for a single OSN. Such widespread reach and popularity make OSNs a powerful tool for communication, especially during national and international events of interest, like sports, natural calamities, political events, etc. Online social networks Is the primary source of information in form of news, updates, blogs, etc.

Multimedia based SNS allows organization, sharing and embedding of content and profile/attribute information like images, videos and corporate media videos like video clips, music videos or short documentary etc. like YouTube. Best suits the information need to bloggers, researchers and other online communities to host images, videos and other social media. The above listed applications are the most popularly used and considered to be the conventional part of the OSN. It is to be noted that the distinctions among the different categories of social media are getting blurred. For example, social network sites and Multimedia based OSN overlap more and more.

Alongside the exploding popularity of the social networks, it raises some issues and challenges as well. It is worth mentioning that the socio-cultural ecosystem of the social media is complex as new services are created dynamically and further, constant changes to communication between people, groups and organizations also add complexity to the system. In this virtual age the services offered by the social communication networks are the important components of the digital image. Due to massive development in the online social network the size of the user footprint in online services is also increasing (Malhotra et al., 2012). The user interacts with the friends, post the updates, write blogs, tag online resources, etc. The online digital footprints capture the user online identity and helps in providing the identity based on the works done in the network.

The online blogs and the digital footprints remain forever. By having strong relationship between the user and their identity the online unique identification of the user can be processed (Golder et al. 2014). Linking of multiple user profile facilitates the analysis across the different social networks. This leads to security issues over the innumerable privacy and security threats that arise due to enormous volume of the information obtainable about the user. The social network users choose the username as per their wish to which totally differs from their real identity. Apparently, users may choose representations/phony usernames for each social media service (Kim et al., 2010). The data mining approach in social media is achieved by numerous researchers in their research works. The extraction of appropriate data profile from the social network such as Facebook and LinkedIn based on user’s search criteria. This is the basis of user’s intent of querying the search which is the major concern of this research. The linking, identifying and extracting information from the multiple social networks with respect to their publicly available attributes of a user is the overall aim of this research.

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