Natural Tragedy Commendation Hasty Alert Using Tweet Events Over Distributed Processing Framework

An Event processing is the scheme of streams that related with information (data) about things that happen (events), and deriving a conclusion from tweet in real time. Twitter is a social network platform that consists of billions of users all over the world where people collaborate and Share information related to real world events. An important characteristic of Twitter is its real-time nature and also investigate the real-time interaction of events such as cyclones in Twitter and propose a framework to monitor tweets to detect a target event. These large scales tweet data processing are done by placing those tweet events in a distributed system. The server processes the tweet queue and executes the operations based on it. An devise classifier of tweets based on features such as the keywords in a tweet, the number of character, the number of words, and their context. The status update which almost pinpoints what is happening in and around an individual user and also tracks the user location. This small content with real world information when processed with some statistical tool may assist us to predict a live occurring event (e.g. cyclone) and regard each twitter user as a feeler and apply particle filtering, which are widely used for location estimation. Tweet in the message queue is done by Apache Kafka which is a distributed publish-subscribe messaging queue system. These frameworks will parallelize our computations over a cluster of machines

Interneti võimalused ja ohud: noorte online-praktikate mõju nende subjektiivsele heaolule

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Teismelised on ühed kõige aktiivsemad internetikasutajad ja internet moodustab loomuliku osa nende igapäevaelust. Kuna internet on siiski suhteliselt uus meedium, mille kasutust ei raamista väga kindlad normid, kuid mille noored on väga kiirelt ja aktiivselt omaks võtnud, ärgitab see küsima, millist mõju internetikasutus noortele avaldab – kas positiivset või negatiivset. Heaolu kontseptsioonist lähtudes on doktoritöös vaatluse all nii internetikasutuse positiivsed kui ka negatiivsed küljed ning nende mõju noorte elukvaliteedile. Viimane aspekt on eriti oluline, kuna teismeiga on üks olulisemaid arenguperioode. Doktoritöös olid vaatluse all noorte online-praktikad – ühelt poolt blogimine kui positiivne ja teiselt poolt ülemäärane internetikasutus kui problemaatiline praktika – ning see, kuidas ja missugustel tingimustel need suurendavad või vähendavad noore heaolu. Nii meediumi valikut kui kasutust kujundavad laiemad kontekstuaalsed tegurid nagu vanus, sugu ja sotsiaalne keskkond (näiteks suhted pere ja eakaaslastega) ning ühiskondlikud tingimused (kultuuriline tasand), milles inimene elab, aga ka meediumi enda või selle rakenduste omadused. Seega võib järeldada, et just kontekst loob ja määrab internetikasutuse võimalikud positiivsed või negatiivsed tulemid. Internetikasutusel võivad olla erinevad tagajärjed. Näiteks avaldavad noored blogides enamasti tõele vastavat sisu, millega nad kujundavad enda identiteeti ja hoiavad sotsiaalseid suhteid, või mis pakub võimalust pälvida tunnustust eakaaslaste hulgas. Samas jagavad noored blogis enda kohta intiimset infot, millel võivad olla negatiivsed tagajärjed. Ülemäärane internetikasutus on seotud nii psühholoogiliste probleemide, internetis veedetava aja kui ka noore digitaalsete oskustega ja sellega, mida ta online-keskkonnas teeb. Ülemäärane internetikasutus võib olla ühelt poolt toimetulekustrateegia, saamaks üle negatiivsetest emotsioonidest, kuna just noortele ekspertkasutajatele pakub internet mitmesuguseid võimalusi meelelahutuseks ja tujutõstmiseks. Teiselt poolt võib see toimetulekumehhanism avaldada pikemas perspektiivis noore heaolule negatiivset mõju.Teenagers have become the most prominent users of the Internet as they effortlessly incorporate the medium into their everyday lives. Due to the newness of the medium, only partially settled norms surrounding usage, and intensity with which the online space was adopted by the youth, much attention has been paid to dwell upon whether the usage of the Internet by the young people brings along positive or negative outcomes. The concept of well-being is used in the thesis to simultaneously look both at the positive and negative aspects of Internet use and to ask how these phenomena are related to young people’s quality of life. The latter question is especially important as adolescence is the formative period in young people’s development. The thesis looked at online practices – blogging as a positive side, and excessive Internet use as a problematic one – and how and in what condition they increase or decrease the well-being of the young. The findings suggest that both media choice and usage, as well as the well-being of the young Internet users, are framed by larger contextual factors – age and gender of the user; social environment (e.g. family and peer influence) and societal (cultural level) conditions individuals live in; and the structural characteristics of the medium or its applications. Hence, the thesis suggests that it is the context which creates and defines the positivity and negativity of certain outcomes of Internet usage. For instance, adolescent bloggers primarily stay truthful to their offline selves in their blogs, and hence the practice could be seen as a mechanism for maintaining one’s identity and social contacts, but also as an opportunity to seek prestige and competence among the peer group. At the same time, revealing intimate details about one’s life in a blog can also lead to possible negative consequences. Excessive Internet use among the young is related to psychological distress and the time spent online but also to one’s digital skills and the activities one engages in online. Hence, on the one hand, excessive Internet use may be a coping strategy, especially for more expert young users of the medium, as it offers a wide range of opportunities for mood management and entertainment; on the other hand, it may have negative outcomes on one’s well-being in the long run

A Review on Opinion Mining: Approaches, Practices and Application

Opinion Mining also known as Sentiment Analysis (SA) has recently become the focus of many researchers, because analysis of online text is useful and demanded in many different applications. Analysis of social sentiments is a trending topic in this era because users share their emotions in more suitable format with the help of micro blogging services like twitter. Twitter provides information about individual's real-time feelings through the data resources provided by persons. The essential task is to extract user's tweets and implement an analysis and survey. However, this extracted information can very helpful to make prediction about the user's opinion towards specific policies. The motive of this paper is to perform a survey on sentiment analysis algorithms that shows the utilizing of different ML and Lexicon investigation methodologies and their accuracy. Our paper also focuses on the three kinds of machine learning algorithms for Sentiment Analysis- Supervised, Unsupervised Algorithms

Social media mining for identification and exploration of health-related information from pregnant women

Widespread use of social media has led to the generation of substantial amounts of information about individuals, including health-related information. Social media provides the opportunity to study health-related information about selected population groups who may be of interest for a particular study. In this paper, we explore the possibility of utilizing social media to perform targeted data collection and analysis from a particular population group -- pregnant women. We hypothesize that we can use social media to identify cohorts of pregnant women and follow them over time to analyze crucial health-related information. To identify potentially pregnant women, we employ simple rule-based searches that attempt to detect pregnancy announcements with moderate precision. To further filter out false positives and noise, we employ a supervised classifier using a small number of hand-annotated data. We then collect their posts over time to create longitudinal health timelines and attempt to divide the timelines into different pregnancy trimesters. Finally, we assess the usefulness of the timelines by performing a preliminary analysis to estimate drug intake patterns of our cohort at different trimesters. Our rule-based cohort identification technique collected 53,820 users over thirty months from Twitter. Our pregnancy announcement classification technique achieved an F-measure of 0.81 for the pregnancy class, resulting in 34,895 user timelines. Analysis of the timelines revealed that pertinent health-related information, such as drug-intake and adverse reactions can be mined from the data. Our approach to using user timelines in this fashion has produced very encouraging results and can be employed for other important tasks where cohorts, for which health-related information may not be available from other sources, are required to be followed over time to derive population-based estimates.Comment: 9 page

Targeting HIV-related Medication Side Effects and Sentiment Using Twitter Data

We present a descriptive analysis of Twitter data. Our study focuses on extracting the main side effects associated with HIV treatments. The crux of our work was the identification of personal tweets referring to HIV. We summarize our results in an infographic aimed at the general public. In addition, we present a measure of user sentiment based on hand-rated tweets

Event Detection on Twitter

Detecting events by using social media has been an active research problem. In this work, we investigate and compare the performance of two methods for event detection in Twitter by using Apache Storm as the stream processing infrastructure. The first event detection method is based on identifying uncommonly common words inside tweet blocks, and the second one is based on clustering tweets to detect a cluster as an event. Each of the methods has its own characteristics. Uncommonly common word based method relies on the burst of words and hence is not affected from concurrency problems in distributed environment. On the other hand, clustering based method includes a finer grained analysis, but it is sensitive to the concurrent processing. We investigate the effect of stream processing and concurrency handling support provided by Apace Storm on event detection by these methods

An Unprecedented Approach of Detecting and Reporting System of Earthquakes Using Tweet Analysis

Social media has got an exponential growth in recent years. One of the most representative examples is Twitter, which allows users to publish short tweets (messages within a 140-character limit) about “what’s happening”. This paper focuses on detecting those events to have a better understanding of what users are really discussing about in Twitter. Event detection has long been a research topic. The underlying assumption is that some related words would show an increase in the usage when an event is happening. An event is therefore conventionally represented by a number of keywords showing burst in appearance count. In this paper, we investigated the real-time nature of Twitter, devoting particular attention to event detection like earthquake. We developed an earthquake reporting system that extracts earthquakes from Twitter. It is possible to detect an earthquake by monitoring tweets. Our system detects an earthquake occurrence and sends an e-mail, possibly before an earthquake actually arrives at a certain location. This paper is the first of its kind using social media for detecting natural calamities

The Future of Connection : Serendipity and Control in Interpersonal Communication Tools

This foresight project explored the contemporary trends and tensions inherent in people's experiences with and using interpersonal communication tools. A standard foresight process was overlaid with an experiential lens in order to provide technology designers with useful insights. The outcomes of this project include four tools intended for designers of interpersonal communication applications. These tools include a map of experiential tensions, a landscape of contemporary behaviour, a set of four future scenarios and implications of each, and finally a set of ten reflection questions intended to provoke critical thought about the choices designers make about the balance between serendipity and control in interpersonal communication tools

SOCIAL MEDIA AND CHANGING COMMUNICATION PATTERNS AMONG STUDENTS: AN ANALYSIS OF TWITTER USE BY UNIVERSITY OF JOS STUDENTS

The developments in Internet technology have seen a rapid rise and change in information flow in contemporary society. One such significant development is the popularity of social network sites, an innovation that is redefining the process of sharing mediated messages. Twitter, an online social networking and micro blogging service that enables users to send and read "tweets", has over 500 million users who send over 400 million tweets daily, with nearly 60% of tweets sent from mobile devices. Regarded as ―the SMS of the Internet‖ and one of the ten most visited websites, its users tweet about any topic within the 140-character limit and follow others. The paper set out to study the topological characteristics of Twitter, its power as a new medium of information sharing and social convergence, and dimensions of usage by students of the University of Jos. Anchored on the Uses and Gratifications theory, data was collated from the field through questionnaire. Results show that the medium represents both a social forum and a news outlet to the students. Based on this, it was recommended that users should endeavour to verify messages or tweets and sources before sharing with others.Keywords: Twitter, Social Media, Social Networking Sites (SNSs), Tweet, Internet, Student