Information Contagion through Social Media: Towards a Realistic Model of the ...Axel Bruns
Paper by Axel Bruns, Patrik Wikström, Peta Mitchell, Brenda Moon, Felix Münch, Lucia Falzon, and Lucy Resnyansky presented at the ACSPRI 2016 conference, Sydney, 19-22 July 2016/
Information Contagion through Social Media: Towards a Realistic Model of the ...Axel Bruns
Paper by Axel Bruns, Patrik Wikström, Peta Mitchell, Brenda Moon, Felix Münch, Lucia Falzon, and Lucy Resnyansky presented at the ACSPRI 2016 conference, Sydney, 19-22 July 2016/
Recommendations for usage tracking for research networking systems, v.1. July...lesliey
List of recommendations for usage tracking and analysis for institutions with research networking systems such as VIVO, Profiles or SciVal Experts. Version 1 of these recommendations was authored by a subgroup of the CTSA Research Networking Affinity Group (Wash U, Elsevier, UCSF).
A Study of User Interaction with Context Aware Notifications from a Moodle Le...Periquest Ltd
This paper reports on a user study to gauge user interaction with RSS based mobile electronic updates from a Moodle based virtual learning environment. The mobile reception of such information can be received in three dimensions of context: time, location and activity. With the active participation of fifteen students, the project aims to compare and evaluate the effectiveness of these context dimensions by comparing the level of user engagement initially across one academic term. The mobile updates relate to teaching material, course work feedback, and general announcements from academic staff across the University’s academic departments. As well as user profiling when interaction with the updates, early investigations show that there exists peak times when users interact with these applications. Initial results indicate that interactions occurred generally during office hours and within the confines of the campus environment, although uses of the activity based application were recorded also in informal locations outside of working hours. The results also show that time based electronic updates are the most popular, engagement wise, when compared to location and activity.
Net spam a network based spam detection framework for reviews in online socia...CloudTechnologies
Net spam a network based spam detection framework for reviews in online social media is an M-Tech IEEE 2017 Java Data Mining Project B-tech Major Project CSE Main Project
Recommendations for usage tracking for research networking systems, v.1. July...lesliey
List of recommendations for usage tracking and analysis for institutions with research networking systems such as VIVO, Profiles or SciVal Experts. Version 1 of these recommendations was authored by a subgroup of the CTSA Research Networking Affinity Group (Wash U, Elsevier, UCSF).
A Study of User Interaction with Context Aware Notifications from a Moodle Le...Periquest Ltd
This paper reports on a user study to gauge user interaction with RSS based mobile electronic updates from a Moodle based virtual learning environment. The mobile reception of such information can be received in three dimensions of context: time, location and activity. With the active participation of fifteen students, the project aims to compare and evaluate the effectiveness of these context dimensions by comparing the level of user engagement initially across one academic term. The mobile updates relate to teaching material, course work feedback, and general announcements from academic staff across the University’s academic departments. As well as user profiling when interaction with the updates, early investigations show that there exists peak times when users interact with these applications. Initial results indicate that interactions occurred generally during office hours and within the confines of the campus environment, although uses of the activity based application were recorded also in informal locations outside of working hours. The results also show that time based electronic updates are the most popular, engagement wise, when compared to location and activity.
Net spam a network based spam detection framework for reviews in online socia...CloudTechnologies
Net spam a network based spam detection framework for reviews in online social media is an M-Tech IEEE 2017 Java Data Mining Project B-tech Major Project CSE Main Project
We are providing training on IEEE 2016-17 projects for Ph.D Scalars, M.Tech, B.E, MCA, BCA and Diploma students for
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Dialectal Arabic sentiment analysis based on tree-based pipeline optimizatio...IJECEIAES
The heavy involvement of the Arabic internet users resulted in spreading data written in the Arabic language and creating a vast research area regarding natural language processing (NLP). Sentiment analysis is a growing field of research that is of great importance to everyone considering the high added potential for decision-making and predicting upcoming actions using the texts produced in social networks. Arabic used in microblogging websites, especially Twitter, is highly informal. It is not compliant with neither standards nor spelling regulations making it quite challenging for automatic machine-learning techniques. In this paper’s scope, we propose a new approach based on AutoML methods to improve the efficiency of the sentiment classification process for dialectal Arabic. This approach was validated through benchmarks testing on three different datasets that represent three vernacular forms of Arabic. The obtained results show that the presented framework has significantly increased accuracy than similar works in the literature.
Behavioural Modelling Outcomes prediction using Casual FactorsIJMER
Generating models from large data sets—and deter-mining which subsets of data to
mine—is becoming increasingly automated. However choosing what data to collect in the first place
requires human intuition or experience, usually supplied by a domain expert. This paper describes a
new approach to machine science which demonstrates for the first time that non-domain experts can
collectively formulate features, and provide values for those features such that they are predictive of
some behavioral outcome of interest. This was accomplished by building a web platform in which
human groups interact to both respond to questions likely to help predict a behavioral outcome and
pose new questions to their peers. This results in a dynamically-growing online survey, but the result
of this cooperative behavior also leads to models that can predict user's outcomes based on their
responses to the user-generated survey questions. Here we describe two web-based experiments that
instantiate this approach: the first site led to models that can predict users' monthly electric energy
consumption; the other led to models that can predict users' body mass index. As exponential
increases in content are often observed in successful online collaborative communities, the proposed
methodology may, in the future, lead to similar exponential rises in discovery and insight into the
causal factors of behavioral outcomes
Social Media Datasets for Analysis and Modeling Drug Usageijtsrd
This paper based on the research carried out in the area of data mining depends for managing bulk amount of data with mining in social media on using composite applications for performing more sophisticated analysis. Enhancement of social media may address this need. The objective of this paper is to introduce such type of tool which used in social network to characterised Medicine Usage. This paper outlined a structured approach to analyse social media in order to capture emerging trends in medicine abuse by applying powerful methods like Machine Learning. This paper describes how to fetch important data for analysis from social network. Then big data techniques to extract useful content for analysis are discussed. Sindhu S. B | Dr. B. N Veerappa "Social Media Datasets for Analysis and Modeling Drug Usage" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25246.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/25246/social-media-datasets-for-analysis-and-modeling-drug-usage/sindhu-s-b
A Decision Support System for Inbound Marketers: An Empirical Use of Latent D...Meisam Hejazi Nia
Infographic is a type of information presentation that inbound marketers use. I suggest a method that can allow the infographic designers to benchmark their design against the previous viral infographics to measure whether a given design decision can help or hurt the probability of the design becoming viral.
Cyber bullying Detection based on Semantic-Enhanced Marginalized Denoising Au...dbpublications
As a side effect of increasingly popular social media, cyberbullying has emerged as a serious problem afflicting children, adolescents and young adults. Machine learning techniques make automatic detection of bullying messages in social media possible, and this could help to construct a healthy and safe social media environment. In this meaningful research area, one critical issue is robust and discriminative numerical representation learning of text messages. In this paper, we propose a new representation learning method to tackle this problem. Our method named Semantic-Enhanced Marginalized Denoising Auto-Encoder (smSDA) is developed via semantic extension of the popular deep learning model stacked denoising autoencoder. The semantic extension consists of semantic dropout noise and sparsity constraints, where the semantic dropout noise is designed based on domain knowledge and the word embedding technique. Our proposed method is able to exploit the hidden feature structure of bullying information and learn a robust and discriminative representation of text. Comprehensive experiments on two public cyberbullying corpora (Twitter and MySpace) are conducted, and the results show that our proposed approaches outperform other baseline text representation learning methods..
M.Phil Computer Science Wireless Communication ProjectsVijay Karan
List of Wireless Communication IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Wireless Communication for M.Phil Computer Science students.
M.E Computer Science Wireless Communication ProjectsVijay Karan
List of Wireless Communication IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Wireless Communication for M.E Computer Science students.
M.Phil Computer Science Parallel and Distributed System ProjectsVijay Karan
List of Parallel and Distributed System IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for M.Phil Computer Science students.
M.E Computer Science Parallel and Distributed System ProjectsVijay Karan
List of Parallel and Distributed System IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for M.E Computer Science students.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
IEEE 2014 ASP.NET with VB Projects
1. IEEE 2014 ASP.NET with VB Projects
Web : www.kasanpro.com Email : sales@kasanpro.com
List Link : http://kasanpro.com/projects-list/ieee-2014-asp-net-with-vb-projects
Title :Mining Social Media Data for Understanding Student's Learning Experiences
Language : ASP.NET with VB
Project Link :
http://kasanpro.com/p/asp-net-with-vb/mining-social-media-data-understanding-students-learning-experiences
Abstract : Students' informal conversations on social media (e.g. Twitter, Facebook) shed light into their educational
experiences - opinions, feelings, and concerns about the learning process. Data from such uninstrumented
environment can provide valuable knowledge to inform student learning. Analyzing such data, however, can be
challenging. The complexity of student's experiences reflected from social media content requires human
interpretation. However, the growing scale of data demands automatic data analysis techniques. In this paper, we
developed a workflow to integrate both qualitative analysis and large - scale data mining techniques. We focus on
engineering student's Twitter posts to understand issues and problems in their educational experiences. We first
conducted a qualitative analysis on samples taken from about 25,000 tweets related to engagement, and sleep
deprivation. Based on these results, we implemented a multi - label classification algorithm to classify tweets
reflecting student's problems. We then used the algorithm to train a detector of student problems from about 35,000
tweets streamed at the geo - location of Purdue University. This work, for the first time, presents a methodology and
results that show how informal social media data can provide insights into students' experiences.
Title :Cost-effective Viral Marketing for Time-critical Campaigns in Large-scale Social Networks
Language : ASP.NET with VB
Project Link : http://kasanpro.com/p/asp-net-with-vb/viral-marketing-cost-effective-time-critical-campaigns-large-scale-social-n
Abstract : Online social networks (OSNs) have become one of the most effective channels for marketing and
advertising. Since users are often influenced by their friends, "wordof- mouth" exchanges, so-called viral marketing, in
social networks can be used to increase product adoption or widely spread content over the network. The common
perception of viral marketing about being cheap, easy, and massively effective makes it an ideal replacement of
traditional advertising. However, recent studies have revealed that the propagation often fades quickly within only few
hops from the sources, counteracting the assumption on the self-perpetuating of influence considered in literature.
With only limited influence propagation, is massively reaching customers via viral marketing still affordable? How to
economically spend more resources to increase the spreading speed? We investigate the cost-effective massive viral
marketing problem, taking into the consideration the limited influence propagation. Both analytical analysis based on
power-law network theory and numerical analysis demonstrate that the viral marketing might involve costly seeding.
To minimize the seeding cost, we provide mathematical programming to find optimal seeding for medium-size
networks and propose VirAds, an efficient algorithm, to tackle the problem on largescale networks. VirAds guarantees
a relative error bound of O(1) from the optimal solutions in power-law networks and outperforms the greedy heuristics
which realizes on the degree centrality. Moreover, we also show that, in general, approximating the optimal seeding
within a ratio better than O(log n) is unlikely possible.