A Study on Sentiment Analysis on Social Media Data

Manasa, Koppula; Padma, M. C.

doi:10.1007/978-981-13-5802-9_58

Cited by 4 publications

(5 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Generally speaking, there are four main approaches in sentiment analysis which are machine learning, ,lexiconbased, statistical and rule-based (Manasa & Padma, 2019). in this paper we use rule-based approach to analysis the opinion of Twitter users regarding a particular topic.…”

Section: Methodsmentioning

confidence: 99%

“…to analyze social media data, a survey of tools and techniques used for different purposes such as mental health diagnostics to marketing and movement tracking is presented in (Batrinca & Treleaven, 2015). The authors of (Manasa & Padma, 2019) have studied the sentiment analysis tools and processes and have proposed a number of steps to guide the analysis process. They also highlight the use of machine learning as an important tool for sentiment analysis.…”

Section: Researchers Have Utilized Various Tools and Approachesmentioning

confidence: 99%

“…The availability of this real and freely available data, which can be acquired with minimal efforts, has encouraged researchers to analyse it and harness its potential in areas such as marketing, decision making and predicting the future ( Analyzing social media data is carried out for many purposes, one of which is sentiment analysis, where users' comments posted on social media about a particular topic is processed and classed into positive, negative and neutral opinions. Based on the analysis results, further actions can be taken, for example change the course of a process or continue or not continue with the process (Manasa & Padma, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…There are many instances of social media in use, such as Facebook, Twitter and Instagram; according to (Manasa & Padma, 2019) Twitter is the most popular one for data collection purposes by researchers; due to the fact that it is a general-purpose medium which covers data from a wide spectrum of fields. Authors of (Ratkiewicz et al, 2011) claim that Twitter has grabbed researcher's attention due to its popular use and transparent data sharing policy.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Querying Social Media to Track People’s Movements and Discussions Via a Browser Interface

Tahir

Mahmud

2020

ACAD J NAWROZ UNIV

View full text Add to dashboard Cite

Social networking is micro-blogging site where users post short text-based messages. These messages often relate to a particular topic, event or product and are frequently coupled with the authors’ opinion. This information provides an exciting opportunity for individuals and companies who might benefit from being able to collate and analyze the data to discover opinion on an item of interest. This paper reports on the outcome of a project that aims to produce a web page that queries the social Web (specifically Twitter.com and Foursquare.com.) through the available APIs to track people’s movements and the topic of their discussions. Tweets will be the main data source and queries results will be ranked and sorted out by total frequency in a Web accessible MySQL database. The result shows that the system has been successful in achieving the set aims.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Researchers Have Utilized Various Tools and Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Querying Social Media to Track People’s Movements and Discussions Via a Browser Interface

Tahir

Mahmud

2020

ACAD J NAWROZ UNIV

View full text Add to dashboard Cite

show abstract

“…Sentiment analysis "considers the computational treatment of subjective information contained in text" [5]. Understanding public opinion, for example, empowers institutions to make data-driven, strategic choices [6]; analyzing customers' sentiment through sentiment analysis can guide product development decisions such as customers' needs and preferences. Similarly, political campaigns can leverage sentiment analysis to refine their messaging and outreach strategies.…”

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis in Social Media: A Case Study of Hike in University School Fees in Selected Nigerian Universities

Aremu,

Muhammad

2024

JIWE

View full text Add to dashboard Cite

Faced with escalating operational costs and government disinvestment, Nigerian public universities are implementing tuition fee increases to maintain institutional functionality. This necessary fiscal measure comes in the wake of 2022 industrial action, which exacerbated pre-existing financial strain through extended work stoppages and potentially higher costs associated with resuming activities, while leaving unaddressed the longstanding demands of academics for improved welfare and working conditions. The court-mandated resumption of academic activities without resolution of these core issues further strained university finances, leading to a significant increase in tuition fees. Using VADER, this study investigated social media sentiments related to the increase in university school fees at Usmanu Danfodiyo University, Sokoto, and the University of Maiduguri. The results revealed that students' sentiments regarding the rise in tuition fees at the two universities were largely neutral, with 4.6% positive sentiment, 7.9% negative sentiment, and 87.5% neutral sentiment identified for Usmanu Danfodiyo University, Sokoto. In contrast, the University of Maiduguri had 0% positive sentiment, 19.8% negative sentiment, and 80.2% neutral sentiment. The study recommends seeking feedback through surveys or student leaders and offering scholarships to indigent students to address fee hike concerns at the two universities. While VADER is designed to handle social media textual data, few misclassifications of sentiments were noted and discussed.

show abstract

Review of Current Machine Learning Approaches for Anomaly Detection in Network Traffic

Ali

Manasa

Aljunid

et al. 2020

JTDE

View full text Add to dashboard Cite

Due to the advance in network technologies, the number of network users is growing rapidly, which leads to the generation of large network traffic data. This large network traffic data is prone to attacks and intrusions. Therefore, the network needs to be secured and protected by detecting anomalies as well as to prevent intrusions into networks. Network security has gained attention from researchers and network laboratories. In this paper, a comprehensive survey was completed to give a broad perspective of what recently has been done in the area of anomaly detection. Newly published studies in the last five years have been investigated to explore modern techniques with future opportunities. In this regard, the related literature on anomaly detection systems in network traffic has been discussed, with a variety of typical applications such as WSNs, IoT, high-performance computing, industrial control systems (ICS), and software-defined network (SDN) environments. Finally, we underlined diverse open issues to improve the detection of anomaly systems.

show abstract

A Study on Sentiment Analysis on Social Media Data

Cited by 4 publications

References 9 publications

Querying Social Media to Track People’s Movements and Discussions Via a Browser Interface

Querying Social Media to Track People’s Movements and Discussions Via a Browser Interface

Sentiment Analysis in Social Media: A Case Study of Hike in University School Fees in Selected Nigerian Universities

Review of Current Machine Learning Approaches for Anomaly Detection in Network Traffic

Contact Info

Product

Resources

About