scholarly journals Real-time tracking and mining of users’ actions over social media

2020 ◽  
Vol 17 (2) ◽  
pp. 403-426
Author(s):  
Ejub Kajan ◽  
Noura Faci ◽  
Zakaria Maamar ◽  
Mohamed Sellami ◽  
Emir Ugljanin ◽  
...  
Keyword(s):  
Social Media ◽  
Web 2.0 ◽  
Sentiment Analysis ◽  
Real Time ◽  
Data Analytics ◽  
Web 2.0 Technologies ◽  
Media Companies ◽  
Real Time Tracking

With the advent of Web 2.0 technologies and social media, companies are actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about what, when, and how to respond to users? actions over social media. Questions that Social Miner allows to answer include what actions were frequently executed and why certain actions were executed more than others.

Realism 2.0

2019 ◽  
pp. 663-679
Author(s):  
Augusta Rohrbach
Keyword(s):  
Web 2.0 ◽  
Knowledge Sharing ◽  
Real Time ◽  
Social Reform ◽  
Data Modeling ◽  
Political Consciousness ◽  
Web 2.0 Technologies ◽  
Reform Agenda ◽  
Social Purpose ◽  
The Social

This chapter looks to the future of teaching realism with Web 2.0 technologies. After discussing the ways in which technologies of data modeling can reveal patterns for interpretation, the chapter examines how these technologies can update the social-reform agenda of realism as exemplified by William Dean Howells’s attempted intervention into the Haymarket Riot in 1886. The advent of Web 2.0 techologies offers students a way to harness the genre’s sense of social purpose to knowledge-sharing mechanisms to create a vehicle for political consciousness-raising in real time. The result is “Realism 2.0,” a realism that enables readers to engage in their world, which is less text-centric than it was for previous writers.

Cloud Computing Technologies for Open Connected Government

2016 ◽  
pp. 1-14 ◽  
Author(s):  
Zaigham Mahmood
Keyword(s):  
Social Media ◽  
Cloud Computing ◽  
Web 2.0 ◽  
Real Time ◽  
Distributed Applications ◽  
Mobile Technologies ◽  
Computing Technologies ◽  
Cloud Technologies ◽  
Cloud Resources

Cloud Computing is an attractive paradigm for organisations that have a requirement to process large scalable distributed applications. It allows for self-provisioning of cloud resources to develop and host applications as well as acquire storage and networking resources. Connected Government (c-government) is an area where cloud technologies can be effectively used to achieve the benefits that the cloud paradigm promises. Social Media, Web 2.0 and mobile technologies can all help to further enhance the connected government capabilities. Using such technologies, governments and citizens can engage in real time in the electronic participation of a government's functioning. In this chapter, we introduce the cloud paradigm and then discussing the requirements of c-government, we outline how cloud technologies can help to achieve an open and transparent c-government. The aim is to provide the basics of relationship between c-government and cloud computing to set the scene for other contributions in this volume.

scholarly journals Achieving adoption and effective usage of Web 2.0 among employees within Australian government organizations

2016 ◽  
Vol 18 (1) ◽  
pp. 41-63 ◽  
Author(s):  
Mohd Heikal Husin ◽  
Nina Evans ◽  
Gaye Deegan
Keyword(s):  
Social Media ◽  
Theoretical Model ◽  
Web 2.0 ◽  
Security Requirements ◽  
Government Employees ◽  
Web 2.0 Technologies ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Government Organizations ◽  
Management Technology

Purpose – Ensuring effective usage of Web 2.0 within government organisations is not as straightforward as it seems. The organisations should be aware of a number of issues when implementing Web 2.0 internally. This paper introduces a theoretical model that highlights the importance of management, technology and people issues influencing the level of Web 2.0 usage from an internal perspective. The purpose of this paper was to identify and explore these issues in a government context. Design/methodology/approach – This paper uses a mixed-method (qualitative and quantitative) analysis to identify the issues that should be focused on for achieving effective usage of Web 2.0 among government employees. A combination of interviews, surveys and usage data collected from two government organisations was used to gather the data. Findings – The main finding is that, a policy will act as an initial catalyst for culture change and effective usage of Web 2.0 technologies in a government environment. It was also found that it is important to develop an understanding among senior management about the motivation for their employees to utilise Web 2.0 internally. As a result, the proposed theoretical model could assist government organisations in developing effective adoption approaches through identifying their employees’ motivation to adopt Web 2.0 technologies and developing a suitable organisational social media policy. Research limitations/implications – There is the issue of the small number of both qualitative and quantitative respondents within the research. Such limitation is because the research relies solely on the voluntary participation of the employees. This limitation was coupled with the fact that both organisations had different security requirements that had affected the amount and level of feasible information that was accessible to the researchers. Practical implications – This paper extends the understanding of issues applicable to the adoption of Web 2.0 tools from a government organisations’ perspective. The developed theoretical model acts as an adoption guide for organisations to achieve effective Web2.0 tools usage. At the same time, this paper also examines related motivation aspects which higher management should consider while using a new social media or Web 2.0 platform internally. Originality/value – This paper highlights suitable overview approaches for organisations to consider in increasing adoption of Web 2.0 among their employees. This paper also provides an initial foray into identifying other complex issues that may exist within different government organisations in relation to internal technology usage.

scholarly journals AthPPA: A Data Visualization Tool for Identifying Political Popularity over Twitter

Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 312
Author(s):  
Alexandros Britzolakis ◽  
Haridimos Kondylakis ◽  
Nikolaos Papadakis
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Real Time ◽  
Data Visualization ◽  
Visualization Tool ◽  
Political Leaders ◽  
Political Event ◽  
Data Analyst ◽  
Industrial Sectors ◽  
Social Media Platforms

Sentiment Analysis is an actively growing field with demand in both scientific and industrial sectors. Political sentiment analysis is used when a data analyst wants to determine the opinion of different users on social media platforms regarding a politician or a political event. This paper presents Athena Political Popularity Analysis (AthPPA), a tool for identifying political popularity over Twitter. AthPPA is able to collect in-real-time tweets and for each tweet to extract metadata such as number of likes, retweets per tweet etc. Then it processes their text in order to calculate their overall sentiment. For the calculation of sentiment analysis, we have implemented a sentiment analyzer that is able to identify the grammatical issues of a sentence as well as a lexicon of negative and positive words designed specifically for political sentiment analysis. An analytic engine processes the collected data and provides different visualizations that provide additional insights on the collected data. We show how we applied our framework to the three most prominent Greek political leaders in Greece and present our findings there.

Should we be more Social? Law Librarians and Social Media

2009 ◽  
Vol 9 (3) ◽  
pp. 175-181 ◽  
Author(s):  
James Mullan
Keyword(s):  
Social Media ◽  
Web 2.0 ◽  
Web 2.0 Technologies ◽  
Legal Information ◽  
Social Law

AbstractThis article by James Mullan is based on his paper delivered to the BIALL Conference 2009. It examines the role that social media and Web 2.0 technologies can play in the life of the legal information specialist.

scholarly journals Down with the #Dogefather: Evidence of a Cryptocurrency Responding in Real Time to a Crypto-Tastemaker

2021 ◽  
Vol 16 (6) ◽  
pp. 2230-2240
Author(s):  
Michael Cary
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Real Time ◽  
Media Usage ◽  
Saturday Night ◽  
Negative Perceptions ◽  
Saturday Night Live

Recent research in cryptocurrencies has considered the effects of the behavior of individuals on the price of cryptocurrencies through actions such as social media usage. However, some celebrities have gone as far as affixing their celebrity to a specific cryptocurrency, becoming a crypto-tastemaker. One such example occurred in April 2021 when Elon Musk claimed via Twitter that “SpaceX is going to put a literal Dogecoin on the literal moon”. He later called himself the “Dogefather” as he announced that he would be hosting Saturday Night Live (SNL) on 8 May 2021. By performing sentiment analysis on relevant tweets during the time he was hosting SNL, evidence is found that negative perceptions of Musk’s performance led to a decline in the price of Dogecoin, which dropped 23.4% during the time Musk was on air. This shows that cryptocurrencies are affected in real time by the behaviors of crypto-tastemakers.

scholarly journals SCRAPING OF SOCIAL MEDIA DATA USING PYTHON-3 AND PERFORMING DATA ANALYTICS USING MICROSOFT POWER BI.

2020 ◽  
Vol 9 (7) ◽  
pp. 66-79
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Data Analytics ◽  
Marketing Strategies ◽  
Social Media Data ◽  
The Social ◽  
The Right ◽  
Media Data ◽  
Course Of Study

The manifestation of humanity is driven by fulfillment of desires. These desires are satiated by the society and its resources. But after the advent of social media the societal boundaries have shrunken but desires haven’t, hence the desires are now fulfilled through social media. The aforementioned phenomenon was recognized by the business plutocrats very early and have started to satisfy human desires using social media as a tool. But before satisfying the desires, the businesses needs to identify the specific desires of an individual. The identification of specific desires/needs will help the marketing agencies to develop user specific marketing strategies. These desires are explicitly available through the expressions of sentiments in the social media. The sentiment analysis can provide an insight to the desires of an individual. These patterns and insights helps the businesses to market their product to the right person. The sentiments and expressions can be captured using the scraping technique. The aforesaid points highlight’s the course of study followed by this paper and it is to perform data analytics of the social media data scraped using python.

scholarly journals Extraction Opinion of Social Media in Higher Education Using Sentiment Analysis

bit-Tech ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Thomas Edison Tarigan ◽  
Robby C Buwono ◽  
Sri Redjeki
Keyword(s):  
Higher Education ◽  
Social Media ◽  
Sentiment Analysis ◽  
Real Time ◽  
Naive Bayes ◽  
Training Data ◽  
Test Results ◽  
Bayes Classifier ◽  
Tertiary Institution ◽  
Management Performance

The purpose of this research is to extract social media Twitter opinion on a tertiary institution using sentiment analysis. The results of sentiment analysis will provide input to universities as a form of evaluation of management performance in managing institutions. Sentiment analysis generated using the Naïve Bayes Classifier method which is classified into 4 classes: positive, normal, negative and unknown. This study uses 1000 data tweets used for training data needs. The data is classified manually to determine the sentiment of the tweet. Then 20 tweet data is used for testing. The results of this study produce a system that can classify sentiments automatically with 75% test results for sentiment, some obstacles in processing real-time tweets such as duplicate tweets (spam tweets), Indonesian structures that are quite complex and diverse.

Social media content and sentiment analysis on consumer security breaches

2016 ◽  
Vol 23 (4) ◽  
pp. 855-869 ◽  
Author(s):  
Jianqiang Hao ◽  
Hongying Dai
Keyword(s):  
Social Media ◽  
Empirical Study ◽  
Sentiment Analysis ◽  
Real Time ◽  
Public Perception ◽  
Public Awareness ◽  
Content Type ◽  
Security Breaches ◽  
Short Period ◽  
Significant Difference

Purpose Security breaches have been arising issues that cast a large amount of financial losses and social problems to society and people. Little is known about how social media could be used a surveillance tool to track messages related to security breaches. This paper aims to fill the gap by proposing a framework in studying the social media surveillance on security breaches along with an empirical study to shed light on public attitudes and concerns. Design/methodology/approach In this study, the authors propose a framework for real-time monitoring of public perception to security breach events using social media metadata. Then, an empirical study was conducted on a sample of 1,13,340 related tweets collected in August 2015 on Twitter. By text mining a large number of unstructured, real-time information, the authors extracted topics, opinions and knowledge about security breaches from the general public. The time series analysis suggests significant trends for multiple topics and the results from sentiment analysis show a significant difference among topics. Findings The study confirms that social media monitoring provides a supplementary tool for the traditional surveys which are costly and time-consuming to track security breaches. Sentiment score and impact factors are good predictors of real-time public opinions and attitudes to security breaches. Unusual patterns/events of security breaches can be detected in the early stage, which could prevent further destruction by raising public awareness. Research limitations/implications The sample data were collected from a short period of time on Twitter. Future study could extend the research to a longer period of time or expand key words search to observe the sentiment trend, especially before and after large security breaches, and to track various topics across time. Practical implications The findings could be useful to inform public policy and guide companies responding to consumer security breaches in shaping public perception. Originality/value This study is the first of its kind to undertake the analysis of social media (Twitter) content and sentiment on public perception to security breaches.

Potential Power and Problems in Sentiment Mining of Social Media

2013 ◽  
Vol 4 (2) ◽  
pp. 16-26 ◽  
Author(s):  
John Wang ◽  
Qiannong Gu ◽  
Gang Wang
Keyword(s):  
Social Media ◽  
Web 2.0 ◽  
User Generated Content ◽  
Relative Degree ◽  
Web 2.0 Technologies ◽  
The Social ◽  
Sentiment Mining ◽  
The Future ◽  
Social Media Platforms ◽  
Infinite Array

Sentiment mining research has experienced an explosive growth in awareness and demand as Web 2.0 technologies have paved the way for a surge of social media platforms that have significantly and rapidly increased the availability of user generated opinioned text. The power of opinions has long been known and is beginning to be tapped to a fuller potential through sentiment mining research. Social media sites have become a paradise for sentiment providing endless streams of opinioned text encompassing an infinite array of topics. With the potential to predict outcomes with a relative degree of accuracy, sentiment mining has become a hot topic not only to researchers, but to corporations as well. As the social media user base continues to expand and as researchers compete to fulfill the demand for sentiment analytic tools to sift through the endless stream of user generated content, the growth of sentiment mining of social media will continue well into the future with an emphasis on improved reliability, accuracy, and automation.

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