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.

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. 

Mining Big Data for Marketing Intelligence

2017 ◽  
pp. 250-258
Author(s):  
Khadija Ali Vakeel
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Network Analysis ◽  
Word Of Mouth ◽  
Interaction Network ◽  
Big Data Analysis ◽  
Rule Mining ◽  
Self Organizing Maps ◽  
Marketing Intelligence

This chapter elaborates on mining techniques useful in big data analysis. Specifically, it will elaborate on how to use association rule mining, self organizing maps, word cloud, sentiment extraction, network analysis, classification, and clustering for marketing intelligence. The application of these would be on decisions related to market segmentation, targeting and positioning, trend analysis, sales, stock markets and word of mouth. The chapter is divided in two sections of data collection and cleaning where we elaborate on how twitter data can be extracted and mined for marketing decision making. Second part discusses various techniques that can be used in big data analysis for mining content and interaction network.

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