SENTIMENT ANALYSIS AND TOPIC MODELLING ON TWITTER FOR CLEAN INDIA MISSION

This study aims to determine and analyze responses regarding customer satisfaction Ruangguru Application to the learning space features in the Ruangguru Application at every level of education. This is useful to know the strengths and weaknesses of the Ruangguru Application based on sentiment responses from Ruangguru users. Ruangguru is an online tutoring startup and a technology-based educational content service and provider no. 1 in Indonesia. So of course, customer satisfaction is an important thing that is the goal of the company. So that when customer satisfaction is met, that is where the company can realize their goals. To see how the level of customer satisfaction, sentiment analysis methods and topic modeling are used in processing the data so that responses can be seen as to what is provided by the customer so that it can be an evaluation for the Ruangguru Application.

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A Model of Extracting Patterns in Social Network Data Using Topic Modelling, Sentiment Analysis and Graph Databases

Computer Science & Information Technology (CS & IT) ◽

10.5121/csit.2017.70608 ◽

2017 ◽

Author(s):

Assane Wade ◽

Giovanna Di MarzoSerugendo

Keyword(s):

Social Network ◽

Sentiment Analysis ◽

Network Data ◽

Graph Databases ◽

Topic Modelling ◽

Social Network Data

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Mining Tourist's Perception toward Indonesia Tourism Destination Using Sentiment Analysis and Topic Modelling

Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things - CCIOT 2019 ◽

10.1145/3361821.3361829 ◽

2019 ◽

Author(s):

Herry Irawan ◽

Gina Akmalia ◽

Riefvan Achmad Masrury

Keyword(s):

Sentiment Analysis ◽

Topic Modelling ◽

Tourism Destination

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Sentiment Analysis and Topic Modelling of Indian Government’s Twitter Handle #IndiaFightsCorona

Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation - IFIP Advances in Information and Communication Technology ◽

10.1007/978-3-030-64861-9_30 ◽

2020 ◽

pp. 339-351

Author(s):

Christina Sanchita Shah ◽

M. P. Sebastian

Keyword(s):

Sentiment Analysis ◽

Topic Modelling

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Topic Modelling and Sentiment Analysis of Global Warming Tweets

Journal of Organizational and End User Computing ◽

10.4018/joeuc.294901 ◽

2022 ◽

Vol 34 (3) ◽

pp. 1-18

Author(s):

Fang Qiao ◽

Jago Williams

Keyword(s):

Global Warming ◽

Sentiment Analysis ◽

Data Analytics ◽

Positive Emotions ◽

Big Data Analytics ◽

Environmental Issues ◽

Extreme Weather Events ◽

Topic Modelling ◽

Critical View ◽

Weather Events

With the increasing extreme weather events and various disasters, people are paying more attention to environmental issues than ever, particularly global warming. Public debate on it has grown on various platforms, including newspapers and social media. This paper examines the topics and sentiments of the discussion of global warming on Twitter over a span of 18 months using two big data analytics techniques—topic modelling and sentiment analysis. There are seven main topics concerning global warming frequently debated on Twitter: factors causing global warming, consequences of global warming, actions necessary to stop global warming, relations between global warming and Covid-19; global warming’s relation with politics, global warming as a hoax, and global warming as a reality. The sentiment analysis shows that most people express positive emotions about global warming, though the most evoked emotion found across the data is fear, followed by trust. The study provides a general and critical view of the public’s principal concerns and their feelings about global warming on Twitter.

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