scholarly journals Penerapan Text Network Analysis Dalam Menganalisis Pendapat Customer Product Patriot di Shopee

2022 ◽  
Vol 14 (1) ◽  
pp. 72-82
Author(s):  
Ignatius Adrian Mastan ◽  
Yohanes Wendy
Keyword(s):  
Network Analysis ◽  
Social Computing ◽  
Social Contexts ◽  
Consumer Perceptions ◽  
Solid State Drive ◽  
Computing Systems ◽  
Feedback Information ◽  
Customer Feedback ◽  
Selling Process ◽  
Text Network Analysis

E-commerce has changed the buying and selling process and the way people interact via the internet. One company that uses e-commerce is PT Patriot Memory Indonesia. PT Patriot Memory Indonesia sells well-known computer peripherals, including the Solid State Drive (SSD). PT Patriot Memory Indonesia wants to analyze customer feedback regarding SSD products sold in e-commerce, namely Shopee by using Text Network Analysis (TNA) which is one part of social computing. Social computing is a science that focuses on social behavior and social contexts using computing systems. One of the tools of social computing, namely Text Network Analysis (TNA), is a research technique that focuses on identifying and comparing network relationships between words, sentences, and systems to model interactions that generate new knowledge or information. In this study, TextNetwork Analysis will show consumer perceptions through the feedback it provideson buyer reviews. The opinions expressed by consumers in buyer reviews can be analyzed so that they can connect each word and create associations of consumer perceptions of a product. Thus, it can be seen the aspects that must be addressed by the company to improve consumer perceptions. The problem analyzed is the development of social computing in analyzing big data. Can the company take advantage of this information so that they know the perceptions of their consumers through the information in the customer feedback at Shopee. Through Text Network Analysis in social computing, researchers will know the association of each word of consumer perception and can see the perception that has the highest degree of a product and see its relationship with other perceptions. This study looks at consumer perceptions of Patriot SSD products at Shopee. The results of this study can help provide customer feedback information to PT Patriot Memory Indonesia. 

scholarly journals Desi Febriani 175100042p

2019 ◽  
Author(s):  
Desi Febriani
Keyword(s):  
Big Data ◽  
Network Analysis ◽  
Social Computing ◽  
Customer Feedback ◽  
Marketing Intelligence ◽  
Text Network Analysis

Kemajuan teknologi informasi telah membawa peluang bagi bisnis untuk mengembangkan bisnisnya. Pengguna media. Penelitian ini termasuk jenis penelitian kualitatif deskriptif. Penelitian kualitatif deskriptif adalah penelitian yang bertujuan untuk sosial yang semakin meningkat setiap tahunnya menjadikan media sosial menjadi tools perusahaan untuk melihat konsumennya. Perusahaan harus mengetahui analisis media sosial dengan cara yang tepat sesuai dengan rencana bisnis perusahaan. Pemakaian media sosial oleh pengguna telah menghasilkan data jejak keseharian individu dimana terdapat pandangan seseorang terhadap suatu obyek. Data yang terkumpul dengan ukuran yang besar dalam media sosial dan bersifat kompleks tersebut adalah big data. Pemanfaatan social computing dapat digunakan untuk menganalisis pola yang terdapat pada big data. Salah satu tool dari social computing yaitu Text Network Analysis (TNA) adalah teknik penelitian yang berfokus pada identifikasi dan membandingkan hubungan jaringan antara kata, kalimat dan sistem untuk memodelkan interaksi yang menghasilkan pengetahuan atau informasi yang baru. Dalam penelitian ini Text Network Analysis (TNA) akan menunjukkan asosiasi persepsi konsumen melalui customer feedback yang diberikannya pada media social terrhadap e- commerce Consumer to Consumer (C2C) terbesar di Indonesia yaitu Tokopedia dan Bukalapakmendeskripsikan karakteristik dari suatu objek, orang, grup, organisasi atau lingkungan yang menggambarkan situasi atau kejadian tertentu. Data pada penelitian ini yaitu data sekunder dengan cara crawling data pada media sosial Twitter dengan menggunakan metode analisis yaitu Text Network Analysis (TNA). Hasil asosiasi persepsi dari pengolahan data di media sosial melalui Text Network Analysis (TNA) dapat digunakan bisnis e-commerce sebagai marketing intelligence.

THE LANDSCAPE OF INCONSISTENCY: A PERSPECTIVE

2011 ◽  
Vol 05 (03) ◽  
pp. 235-256 ◽  
Author(s):  
DU ZHANG ◽  
ÉRIC GRÉGOIRE
Keyword(s):  
Cloud Computing ◽  
Social Computing ◽  
Special Issue ◽  
Computing Systems ◽  
Semantic Computing

The focus of this introduction to this special issue is to draw a picture as comprehensive as possible about various dimensions of inconsistency. In particular, we consider: (1) levels of knowledge at which inconsistency occurs; (2) categories and morphologies of inconsistency; (3) causes of inconsistency; (4) circumstances of inconsistency; (5) persistency of inconsistency; (6) consequences of inconsistency; (7) metrics for inconsistency; (8) theories for handling inconsistency; (9) dependencies among occurrences of inconsistency; and (10) problem domains where inconsistency has been studied. The take-home message is that inconsistency is ubiquitous and handling inconsistency is consequential in our endeavors. How to manage and reason in the presence of inconsistency presents a very important issue in semantic computing, cloud computing, social computing, and many other data-rich or knowledge-rich computing systems.

scholarly journals Black Lives Matter in Wikipedia: Collaboration and Collective Memory around Online Social Movements

2016 ◽  
Author(s):  
Marlon Twyman ◽  
Brian Keegan ◽  
Aaron Shaw
Keyword(s):  
Social Movements ◽  
Collective Memory ◽  
English Language ◽  
Social Computing ◽  
Computing Systems ◽  
Language Version ◽  
Black Lives Matter ◽  
Prior Literature ◽  
Patterns Of Behavior ◽  
Use Of Social Media

Social movements use social computing systems to complement offline mobilizations, but prior literature has focused almost exclusively on movement actors' use of social media. In this paper, we analyze participation and attention to topics connected with the Black Lives Matter movement in the English language version of Wikipedia between 2014 and 2016. Our results point to the use of Wikipedia to (1) intensively document and connect historical and contemporary events, (2) collaboratively migrate activity to support coverage of new events, and (3) dynamically re-appraise pre-existing knowledge in the aftermath of new events. These findings reveal patterns of behavior that complement theories of collective memory and collective action and help explain how social computing systems can encode and retrieve knowledge about social movements as they unfold.

Sign in / Sign up

Export Citation Format

Share Document