scholarly journals Combining Social Network Analysis and Sentiment Analysis to Explore the Potential for Online Radicalisation

2009 ◽  
Author(s):  
Adam Bermingham ◽  
Maura Conway ◽  
Lisa McInerney ◽  
Neil O'Hare ◽  
Alan F. Smeaton
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Sentiment Analysis

scholarly journals The Behavioral Investigation of Industry 4.0 Concept: A Research On Twitter

2020 ◽  
Vol 4 (2) ◽  
pp. 91-105
Author(s):  
Bulent Cekic
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Sentiment Analysis ◽  
Operations Management ◽  
Industry 4.0 ◽  
Design Research ◽  
Behavioral Operations ◽  
Behavioral Operations Management ◽  
Manufacturing Operations

Abstract: Aim: This paper is going to investigate how Industry 4.0 concept especially the components of it, behaves in social networks and the context of this innovative approach find a place in time in means of content and sentiment comprising. Design / Research methods: Expeditious progress in industrialization and information techniques has made great advancement in developing the next span of production technology. Industry 4.0 is an imperative action where the intention is the alteration of modern production through digitalization and profiteering of the capabilities of new advancements. Today, the absence of powerful appliances still feigns a significant impediment for utilizing the ample potential of Industry 4.0. Notably, behavioral approaches are essential for understanding Industry 4.0, which professes novel trials. This paper briefly surveys the area of Industry 4.0 as it relates to behavioral operations by using sentiment analysis and social network analysis methods and tools by describing features of the relationship network either through numerical and visual representation Conclusions / findings: First of all, it should be presumed that the name Industry 4.0 describes various, fundamentally internet-based developments in manufacturing operations. These advancements do not only have technological but moreover accomplished organizational engagements. Appropriately, a shift from product to service orientation is assumed. Following, the introduction of novel varieties of businesses can be envisioned which embraces new particular functions within the production process sequentially the value-creation networks. Originality / value of the article: Within the context of the current state of the art in operations management literature, this paper fulfills the gap between behavioral operations and industry 4.0 context for the researchers both in operations management and behavioral sciences will benefit from this analysis. Keywords: Behavioral Operations Management, Sentiment Analysis, Industry 4.0, Social Network Analysis. JEL: C88, D23, D24, E71, M11, O14, O33

scholarly journals IMPLEMENTASI SOCIAL NETWORK ANALYSIS DALAM PENYEBARAN INFORMASI VIRUS CORONA (COVID-19) DI TWITTER

2021 ◽  
Vol 2020 (1) ◽  
pp. 292-299
Author(s):  
Dwi Inayah ◽  
Fredy Law Purba
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Sentiment Analysis

Virus Corona (Covid-19) merupakan virus baru yang sudah menyebar ke 215 negara, termasuk Indonesia. Penyebaran yang cepat dan ketidakpastian kapan berakhirnya pandemi Covid-19 ini telah menimbulkan kekhawatiran yang dapat memengaruhi kondisi kesehatan mental masyarakat. Respon kekhawatiran tersebut biasanya diekspresikan ke dalam media sosial, salah satunya twitter. Penelitian ini bertujuan untuk mengidentifikasi kata yang paling sering muncul; mengkategorikan setiap opini yang muncul ke dalam kategori sentimen netral, positif dan negatif; serta mengetahui akun-akun twitter berpengaruh terkait Covid-19. Metode yang digunakan adalah Wordcloud Analysis, Sentiment Analysis, dan Social Network Analysis. Hasil wordcloud analysis menunjukkan bahwa kata yang sering muncul terkait Covid-19 adalah “positif”, “pandemi” dan “Indonesia”. Hasil sentiment analysis menunjukkan bahwa cuitan bersentimen netral merupakan yang terbanyak, disusul cuitan bersentimen negatif, kemudian bersentimen positif. Hasil social network analysis menunjukkan bahwa aktor paling berpengaruh adalah akun @PratiwiHAM. Dengan hasil tersebut, pemerintah dapat melakukan kerja sama dengan akun @PratiwiHAM untuk menyebarkan informasi positif, memberikan dukungan moral, dan menangkal hoax yang diharapkan dapat meningkatkan kondisi kesehatan mental masyarakat Indonesia.

Analysis of Online Social Networks for the Identification of Sarcasm

2018 ◽  
pp. 92-105 ◽  
Author(s):  
Pulkit Mehndiratta
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Sentiment Analysis ◽  
Online Social Networks ◽  
Future Research ◽  
Research Directions ◽  
Textual Data ◽  
Future Research Directions

With the ever-increasing acceptance of online social networks (OSNs), a new dimension has evolved for communication amongst humans. OSNs have given us the opportunity to monitor and mine the opinions of a large number of online active populations in real time. Many diverse approaches have been proposed, various datasets have been generated, but there is a need of collective understanding of this area. Researchers are working around the globe to find a pattern to judge the mood of the user; the still serious problem of detection of irony and sarcasm in textual data poses a threat to the accuracy of the techniques evolved till date. This chapter aims to help the reader to think and learn more clearly about the aspects of sentiment analysis, social network analysis, and detection of irony or sarcasm in textual data generated via online social networks. It argues and discusses various techniques and solutions available in literature currently. In the end, the chapter provides some answers to the open-ended question and future research directions related to the analysis of textual data.

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