Sentiment Analysis of Twitter Data for COVID-19 Lockdown: India Statewise Perspective

Abstract: The whole human race is acquainted with the truth that COVID-19 has taken the form of a pandemic. Almost, all the countries are endeavouring their best to circumscribe the dispersion as much as possible. This paper focuses to observe sentiments of Indians during a nationwide lockdown to find what was going on in people's minds due to lockdown and its extension announced by the Indian government. Data has collected from Twitter during the second lockdown period. The results revealed that the majority of the people shows a positive attitude for declared lockdown and need the extension of the lockdown for a month or two to control the spread across the country. Keywords: COVID-19, Lockdown, Pandemic, Sentiments, Twitter

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Real Time Opinion Mining and Analysis of Twitter Data

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.12.16104 ◽

2018 ◽

Vol 7 (3.12) ◽

pp. 351

Author(s):

K Senthil Kumar ◽

Mohammad Musab Trumboo ◽

Vaibhav . ◽

Satyajai Ahlawat

Keyword(s):

Sentiment Analysis ◽

Opinion Mining ◽

Far East ◽

Lexical Database ◽

Training Set ◽

Twitter Data ◽

The Far East ◽

The People ◽

Single Person ◽

Mass Information

This era, in which we currently stand, is an era of public opinion and mass information. People from all around the globe are joined together through various information junctions to create a global community, where one thing from the far east reaches to the people of the far west within seconds. Nothing is hidden, everything and anything can be scrutinized to its core and through these global criticisms and mass discussions of gigantic magnitude, we have reached to the pinnacle of correct decisions and better choices. These pseudo social groups and data junctions have bombarded our society so much that they now hold the forelock of our opinions and sentiments, ergo, we reach out to these groups to achieve a better outcome. But, all this enormous data and all these opinions cannot be researched by a single person, hence, comes the need of sentiment analysis. In this paper we’ll try to accomplish this by creating a system that will enable us to fetch tweets from twitter and use those tweets against a lexical database which will create a training set and then compare it with the pre-fetched tweets. Through this we will be able to assign a polarity to all the tweets by means of which we can address them as negative, positive or neutral and this is the very foundation of sentiment analysis, so subtle yet so magnificent.

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Sentiment on Twitter Data Set using Recurrent Neural Network - Long Short Term Memory

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.k1244.09811s19 ◽

2019 ◽

Vol 8 (11S) ◽

pp. 1206-1211

Keyword(s):

Social Media ◽

Sentiment Analysis ◽

Language Processing ◽

Short Term Memory ◽

Short Term ◽

Data Set ◽

Term Memory ◽

Twitter Data ◽

The People ◽

Long Short Term Memory

Social media is a combination of different platforms where a huge amount of user-generated data is collected. People from various parts of the country express their opinions, reviews, feedback and marketing strategies through social media such as Twitter, Facebook, Instagram, and YouTube. It is vital to explore, gather data, analyze them and consolidate the people views for better decision making. Sentiment analysis is a natural language processing for information extraction that identifies the user’s views. It is used for extracting reviews and opinions about the satisfaction of products, the events, and people for understanding the current trends of product or user’s behavior. The paper reviews and analyses the existing general approaches and algorithms for sentiment analysis. The proposed system selected to perform sentiment analysis on Twitter data set is Long Short Term Memory [LSTM] and evaluated with Naive Bayes Approach.

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An Approach To Twitter Sentiment Analysis Over Hadoop

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.5.20110 ◽

2018 ◽

Vol 7 (4.5) ◽

pp. 374

Author(s):

Yazala Ritika Siril Paul ◽

Dilipkumar A. Borikar

Keyword(s):

Sentiment Analysis ◽

Opinion Mining ◽

Emotional State ◽

Streaming Data ◽

Data Streaming ◽

Text Data ◽

Twitter Data ◽

The People ◽

Data Platform ◽

Apache Hive

Sentiment analysis is the process of identifying people’s attitude and emotional state from the language they use via any social websites or other sources. The main aim is to identify a set of potential features in the review and extract the opinion expressions of those features by making full use of their associations. The Twitter has now become a routine for the people around the world to post thousands of reactions and opinions on every topic, every second of every single day. It’s like one big psychological database that’s constantly being updated and which can be used to analyze the sentiments of the people. Hadoop is one of the best options available for twitter data sentiment analysis and which also works for the distributed big data, streaming data, text data etc. This paper provides an efficient mechanism to perform sentiment analysis/ opinion mining on Twitter data over Hortonworks Data platform, which provides Hadoop on Windows, with the assistance of Apache Flume, Apache HDFS and Apache Hive.

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How Does the World View China’s Carbon Policy? A Sentiment Analysis on Twitter Data

Energies ◽

10.3390/en14227782 ◽

2021 ◽

Vol 14 (22) ◽

pp. 7782

Author(s):

Ning Xiang ◽

Limao Wang ◽

Shuai Zhong ◽

Chen Zheng ◽

Bo Wang ◽

...

Keyword(s):

Sentiment Analysis ◽

World View ◽

Developed Countries ◽

Carbon Policy ◽

Carbon Neutrality ◽

Twitter Data ◽

Policy Goals ◽

The People ◽

Twitter Users ◽

The Impact

China has recently put forth an ambitious plan to achieve carbon peak around 2030 and carbon neutrality around 2060. However, there are quite a few differences regarding the public views about China’s carbon policy between the Chinese people and the people from other countries, especially concerning the doubt of foreign people about the fidelity of China’s carbon policy goals. Based on Twitter data related to China’s carbon policy topics from 2008 to 2020, this study shows the inter- and intra-annual trends in the count of tweets about China’s carbon policy, conducts sentiment analysis, extracts top frequency words from different attitudes, and analyzes the impact of China’s official Twitter accounts on the global view of China’s carbon policy. Our results show: (1) the global attention to China’s carbon policy gradually rises and occasionally rises suddenly due to important carbon events; (2) the proportion of Twitter users with negative sentiment about China’s carbon policy has increased rapidly and has exceeded the proportion of Twitter users with positive sentiment since 2019; (3) people in developing countries hold more positive or neutral attitudes towards China’s carbon policy, while developed countries hold more negative attitudes; (4) China’s official Twitter accounts serve to improve the global views on China’s carbon policy.

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Sentiment Analysis on Indian Government Schemes Using Twitter data

2019 International Conference on Data Science and Communication (IconDSC) ◽

10.1109/icondsc.2019.8817036 ◽

2019 ◽

Author(s):

V Rekha ◽

R Raksha ◽

Pradnya Patil ◽

N Swaras ◽

G L Rajat

Keyword(s):

Sentiment Analysis ◽

Indian Government ◽

Twitter Data

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Detection of Depression and Mental illness of Twitter users using Machine Learning

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.d8314.049420 ◽

2020 ◽

Vol 9 (4) ◽

pp. 1331-1335

Keyword(s):

Sentiment Analysis ◽

Real Time ◽

Opinion Mining ◽

Communication Tool ◽

The Public ◽

Twitter Data ◽

The People ◽

Document Frequency ◽

Recent Emergence ◽

Twitter Users

Today Micro-blogging has become a popular Internet-user communication tool. Millions of users exchange views on different aspects of their lives. Thus micro blogging websites are a rich source of opinion mining data or Sentiment Analysis (SA) information. Due to the recent emergence of micro blogging, there are a few research works devoted to this subject. We concentrate in our paper on Twitter, one of the prominent micro blogging sites to analyze sentiment of the public. We'll demonstrate, how to gather real-time twitter data for sentiment analysis or opinion mining purposes, and employed algorithms like Term Frequency - Inverse Document Frequency (TF-IDF), Bag of Words (BOW) and Multinomial Naive Bayes ( MNB). We are able to determine positive and negative sentiments for the real-time twitter data using the above chosen algorithms. Experimental evaluations below shows that the algorithms used are efficient and it can be used as a application in detection of the depression of the people. We worked with English in this article, but for any other language it can be used.

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MISTISISME TRADISI MAPPADENDANG DI DESA ALLAMUNGENG PATUE, KABUPATEN BONE

10.31219/osf.io/apz37 ◽

2020 ◽

Author(s):

Askar Nur

Keyword(s):

Qualitative Method ◽

Local Community ◽

Descriptive Study ◽

Ethnographic Approach ◽

The People ◽

Village People ◽

Almost All ◽

The Village

This research explains the mysticism of mappadendang tradition in Allamungeng Patue Village, Bone Regency, which is believed by the local community as a form of shielding from danger and can resist reinforcemen such as Covid-19 outbreak. This research is a descriptive study using qualitative method and an ethnographic approach. This research was carried out with the aim of identifying the mystical space in mappadendang tradition which was held in Allamungeng Patue Village. After conducting the tracing process, the researcher found that mappadendang tradition which was held in Allamungeng Patue Village, Bone Regency in July 2020 was not a tradition of harvest celebration as generally in several villages in Bone Regency, especially Bugis tribe, but mappadendang was held as a form of shielding from all distress including Covid-19 outbreak. This trust was obtained after one of the immigrants who now resides in the village dreamed of meeting an invisible figure (tau panrita) who ordered a party to be held that would bring all the village people because remembering that in the village during Covid-19 happened to almost all the existing areas in Indonesia, the people of Allamungeng Patue Village were spared from the outbreak. Spontaneously, the people of Allamungeng Patue Village worked together to immediately carry out the mappadendang tradition as a form of interpretation of the message carried by the figure.

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