Sentimental Analysis of COVID-19 Tweets Using Deep Learning Models
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Effect of Fireworks, Chinese New Year and the COVID-19 Lockdown on Air Pollution and Public Attitudes
Special Issue on COVID-19 Aerosol Drivers, Impacts and Mitigation (VII) Aerosol and Air Quality Research, 20: 2318–2331, 2020 ISSN: 1680-8584 print / 2071-1409 online Publisher: Taiwan Association for Aerosol Research https://doi.org/10.4209/aaqr.2020.06.0299 Effect of Fireworks, Chinese New Year and the COVID-19 Lockdown on Air Pollution and Public Attitudes Peter Brimblecombe1,2, Yonghang Lai3* 1 Department of Marine Environment and Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan 2 Aerosol Science Research Center, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan 3 School of Energy and Environment, City University of Hong Kong, Hong Kong ABSTRACT Concentrations of primary air pollutants are driven by emissions and weather patterns, which control their production and dispersion. The early months of the year see the celebratory use of fireworks, a week-long public holiday in China, but in 2020 overlapped in Hubei Province with lockdowns, some of > 70 days duration. The urban lockdowns enforced to mitigate the COVID-19 pandemic give a chance to explore the effect of rapid changes in societal activities on air pollution, with a public willing to leave views on social media and show a continuing concern about the return of pollution problems after COVID-19 restrictions are lifted. Fireworks typically give rise to sharp peaks in PM2.5 concentrations, though the magnitude of these peaks in both Wuhan and Beijing has decreased under tighter regulation in recent years, along with general reductions in pollutant emissions. Firework smoke is now most evident in smaller outlying cities and towns. The holiday effect, a reduction in pollutant concentrations when normal work activities are curtailed, is only apparent for NO2 in the holiday week in Wuhan (2015–2020), but not Beijing. -
Text Mining Course for KNIME Analytics Platform
Text Mining Course for KNIME Analytics Platform KNIME AG Copyright © 2018 KNIME AG Table of Contents 1. The Open Analytics Platform 2. The Text Processing Extension 3. Importing Text 4. Enrichment 5. Preprocessing 6. Transformation 7. Classification 8. Visualization 9. Clustering 10. Supplementary Workflows Licensed under a Creative Commons Attribution- ® Copyright © 2018 KNIME AG 2 Noncommercial-Share Alike license 1 https://creativecommons.org/licenses/by-nc-sa/4.0/ Overview KNIME Analytics Platform Licensed under a Creative Commons Attribution- ® Copyright © 2018 KNIME AG 3 Noncommercial-Share Alike license 1 https://creativecommons.org/licenses/by-nc-sa/4.0/ What is KNIME Analytics Platform? • A tool for data analysis, manipulation, visualization, and reporting • Based on the graphical programming paradigm • Provides a diverse array of extensions: • Text Mining • Network Mining • Cheminformatics • Many integrations, such as Java, R, Python, Weka, H2O, etc. Licensed under a Creative Commons Attribution- ® Copyright © 2018 KNIME AG 4 Noncommercial-Share Alike license 2 https://creativecommons.org/licenses/by-nc-sa/4.0/ Visual KNIME Workflows NODES perform tasks on data Not Configured Configured Outputs Inputs Executed Status Error Nodes are combined to create WORKFLOWS Licensed under a Creative Commons Attribution- ® Copyright © 2018 KNIME AG 5 Noncommercial-Share Alike license 3 https://creativecommons.org/licenses/by-nc-sa/4.0/ Data Access • Databases • MySQL, MS SQL Server, PostgreSQL • any JDBC (Oracle, DB2, …) • Files • CSV, txt -
COVID-19: How Hateful Extremists Are Exploiting the Pandemic
COVID-19 How hateful extremists are exploiting the pandemic July 2020 Contents 3 Introduction 5 Summary 6 Findings and recommendations 7 Beliefs and attitudes 12 Behaviours and activities 14 Harms 16 Conclusion and recommendations Commission for Countering Extremism Introduction that COVID-19 is punishment on China for their treatment of Uighurs Muslims.3 Other conspiracy theories suggest the virus is part of a Jewish plot4 or that 5G is to blame.5 The latter has led to attacks on 5G masts and telecoms engineers.6 We are seeing many of these same narratives reoccur across a wide range of different ideologies. Fake news about minority communities has circulated on social media in an attempt to whip up hatred. These include false claims that mosques have remained open during 7 Since the outbreak of the coronavirus (COVID-19) lockdown. Evidence has also shown that pandemic, the Commission for Countering ‘Far Right politicians and news agencies [...] Extremism has heard increasing reports of capitalis[ed] on the virus to push forward their 8 extremists exploiting the crisis to sow division anti-immigrant and populist message’. Content and undermine the social fabric of our country. such as this normalises Far Right attitudes and helps to reinforce intolerant and hateful views We have heard reports of British Far Right towards ethnic, racial or religious communities. activists and Neo-Nazi groups promoting anti-minority narratives by encouraging users Practitioners have told us how some Islamist to deliberately infect groups, including Jewish activists may be exploiting legitimate concerns communities1 and of Islamists propagating regarding securitisation to deliberately drive a anti-democratic and anti-Western narratives, wedge between communities and the British 9 claiming that COVID-19 is divine punishment state. -
Application of Machine Learning in Automatic Sentiment Recognition from Human Speech
Application of Machine Learning in Automatic Sentiment Recognition from Human Speech Zhang Liu Ng EYK Anglo-Chinese Junior College College of Engineering Singapore Nanyang Technological University (NTU) Singapore [email protected] Abstract— Opinions and sentiments are central to almost all human human activities and have a wide range of applications. As activities and have a wide range of applications. As many decision many decision makers turn to social media due to large makers turn to social media due to large volume of opinion data volume of opinion data available, efficient and accurate available, efficient and accurate sentiment analysis is necessary to sentiment analysis is necessary to extract those data. Business extract those data. Hence, text sentiment analysis has recently organisations in different sectors use social media to find out become a popular field and has attracted many researchers. However, consumer opinions to improve their products and services. extracting sentiments from audio speech remains a challenge. This project explores the possibility of applying supervised Machine Political party leaders need to know the current public Learning in recognising sentiments in English utterances on a sentiment to come up with campaign strategies. Government sentence level. In addition, the project also aims to examine the effect agencies also monitor citizens’ opinions on social media. of combining acoustic and linguistic features on classification Police agencies, for example, detect criminal intents and cyber accuracy. Six audio tracks are randomly selected to be training data threats by analysing sentiment valence in social media posts. from 40 YouTube videos (monologue) with strong presence of In addition, sentiment information can be used to make sentiments. -
Respondus Lockdown Browser & Monitor Remote Proctoring Is Available, but Not Recommended. Please Consider Alternative Assess
Respondus Lockdown Browser & Monitor Remote proctoring is available, but not recommended. Please consider alternative assessment strategies. If you absolutely cannot use alternatives, and want to move forward using Respondus Lockdown Browser, here are some aspects to consider to minimize the impact to your students: Definitions: • Respondus Lockdown Browser is an internet browser downloaded and installed by students, which locks down the computer on which they are taking the test so that students cannot open other applications or web pages. Lockdown Browser does not monitor or record student activity. • Respondus Monitor is an instructor-enabled feature of Respondus Lockdown Browser, which uses the students’ webcams to record video and audio of the exam environment. It also records the students’ computer screens. Instructors can view these recordings after the exam session is over. Considerations: • If Respondus Monitor is enabled, students must have a webcam to take the test. Be aware that many of your students may not have access to a webcam. You will need to offer an alternative assessment for students who do not have a webcam. o Students may not be asked to purchase a webcam for these exams, unless one was required as an initial expectation for the course. Requiring the purchase of additional materials not specified in the class description or original syllabus opens up a host of concerns, including but not limited to: student financial aid and ability to pay, grade appeals, and departmental policies. • Both Respondus Lockdown Browser and Respondus Monitor require a Windows or Mac computer. iPads require a specialized app, and are not recommended. -
Text KM & Text Mining
Text KM & Text Mining An Introduction to Managing Knowledge in Unstructured Natural Language Documents Dekai Wu HKUST Human Language Technology Center Department of Computer Science and Engineering University of Science and Technology Hong Kong http://www.cs.ust.hk/~dekai © 2008 Dekai Wu Lecture Objectives Introduction to the concept of Text KM and Text Mining (TM) How to exploit knowledge encoded in text form How text mining is different from data mining Introduction to the various aspects of Natural Language Processing (NLP) Introduction to the different tools and methods available for TM HKUST Human Language Technology Center © 2008 Dekai Wu Textual Knowledge Management Text KM oversees the storage, capturing and sharing of knowledge encoded in unstructured natural language documents 80-90% of an organization’s explicit knowledge resides in plain English (Chinese, Japanese, Spanish, …) documents – not in structured relational databases! Case libraries are much more reasonably stored as natural language documents, than encoded into relational databases Most knowledge encoded as text will never pass through explicit KM processes (eg, email) HKUST Human Language Technology Center © 2008 Dekai Wu Text Mining Text Mining analyzes unstructured natural language documents to extract targeted types of knowledge Extracts knowledge that can then be inserted into databases, thereby facilitating structured data mining techniques Provides a more natural user interface for entering knowledge, for both employees and developers Reduces -
Knowledge-Powered Deep Learning for Word Embedding
Knowledge-Powered Deep Learning for Word Embedding Jiang Bian, Bin Gao, and Tie-Yan Liu Microsoft Research {jibian,bingao,tyliu}@microsoft.com Abstract. The basis of applying deep learning to solve natural language process- ing tasks is to obtain high-quality distributed representations of words, i.e., word embeddings, from large amounts of text data. However, text itself usually con- tains incomplete and ambiguous information, which makes necessity to leverage extra knowledge to understand it. Fortunately, text itself already contains well- defined morphological and syntactic knowledge; moreover, the large amount of texts on the Web enable the extraction of plenty of semantic knowledge. There- fore, it makes sense to design novel deep learning algorithms and systems in order to leverage the above knowledge to compute more effective word embed- dings. In this paper, we conduct an empirical study on the capacity of leveraging morphological, syntactic, and semantic knowledge to achieve high-quality word embeddings. Our study explores these types of knowledge to define new basis for word representation, provide additional input information, and serve as auxiliary supervision in deep learning, respectively. Experiments on an analogical reason- ing task, a word similarity task, and a word completion task have all demonstrated that knowledge-powered deep learning can enhance the effectiveness of word em- bedding. 1 Introduction With rapid development of deep learning techniques in recent years, it has drawn in- creasing attention to train complex and deep models on large amounts of data, in order to solve a wide range of text mining and natural language processing (NLP) tasks [4, 1, 8, 13, 19, 20]. -
The Effect of Lockdown Policies on International Trade Evidence from Kenya
The effect of lockdown policies on international trade Evidence from Kenya Addisu A. Lashitew Majune K. Socrates GLOBAL WORKING PAPER #148 DECEMBER 2020 The Effect of Lockdown Policies on International Trade: Evidence from Kenya Majune K. Socrates∗ Addisu A. Lashitew†‡ January 20, 2021 Abstract This study analyzes how Kenya’s import and export trade was affected by lockdown policies during the COVID-19 outbreak. Analysis is conducted using a weekly series of product-by-country data for the one-year period from July 1, 2019 to June 30, 2020. Analysis using an event study design shows that the introduction of lockdown measures by trading partners led to a modest increase of exports and a comparatively larger decline of imports. The decline in imports was caused by disruption of sea cargo trade with countries that introduced lockdown measures, which more than compensated for a significant rise in air cargo imports. Difference-in-differences results within the event study framework reveal that food exports and imports increased, while the effect of the lockdown on medical goods was less clear-cut. Overall, we find that the strength of lockdown policies had an asymmetric effect between import and export trade. Keywords: COVID-19; Lockdown; Social Distancing; Imports; Exports; Kenya JEL Codes: F10, F14, L10 ∗School of Economics, University of Nairobi, Kenya. Email: [email protected] †Brookings Institution, 1775 Mass Av., Washington DC, 20036, USA. Email: [email protected] ‡The authors would like to thank Matthew Collin of Brookings Institution for his valuable comments and suggestions on an earlier version of the manuscript. 1 Introduction The COVID-19 pandemic has spawned an unprecedented level of social and economic crisis worldwide. -
Safeguarding the Nation's Digital Memory
Mathematics for safeguarding the nation's digital memory Martine J. Safeguarding the nation's digital memory Barons, CMath Archives Martine J. Barons, CMath The digital preservation problem IDSS Director Applied Statistics & Risk Unit The National Archives University of Warwick Project Soft Elicitation [email protected] Data SEJ The Tool ECMI21 13th April 2021 Lessons Lockdown Digital Preservation Awards c Martine J. Barons 2021 Overview Mathematics for safeguarding 1 the nation's Archives digital The digital preservation problem memory Martine J. Barons, 2 IDSS CMath Archives 3 The National Archives Project The digital preservation Soft Elicitation problem Data IDSS The National SEJ Archives Project The Tool Soft Elicitation Data SEJ 4 Lessons The Tool Lockdown Lessons Lockdown Digital Preservation Awards Digital Preservation Awards c Martine J. Barons 2021 What are archives? Mathematics for Collections of information known as records safeguarding the nation's Records digital memory letters Martine J. Barons, reports CMath minutes Archives The digital registers preservation problem maps IDSS The National photographs and films Archives Project digital files Soft Elicitation Data SEJ sound recordings The Tool Lessons Records in an archive are primary sources. Archives provide Lockdown Digital Preservation first-hand information or evidence relating to historical events Awards or figures. c Martine J. Barons 2021 Archives are managed by a variety of types of institutions and the materials they collect differ. Mathematics for Archives safeguarding the nation's Government or national archives: materials related to all digital memory levels of government Martine J. Barons, Corporate archives: manage and preserve business records. CMath College and university archives:preserve materials related Archives to the institution. -
LDA V. LSA: a Comparison of Two Computational Text Analysis Tools for the Functional Categorization of Patents
LDA v. LSA: A Comparison of Two Computational Text Analysis Tools for the Functional Categorization of Patents Toni Cvitanic1, Bumsoo Lee1, Hyeon Ik Song1, Katherine Fu1, and David Rosen1! ! 1Georgia Institute of Technology, Atlanta, GA, USA (tcvitanic3, blee300, hyeoniksong) @gatech.edu (katherine.fu, david.rosen) @me.gatech.edu! !! Abstract. One means to support for design-by-analogy (DbA) in practice involves giving designers efficient access to source analogies as inspiration to solve problems. The patent database has been used for many DbA support efforts, as it is a pre- existing repository of catalogued technology. Latent Semantic Analysis (LSA) has been shown to be an effective computational text processing method for extracting meaningful similarities between patents for useful functional exploration during DbA. However, this has only been shown to be useful at a small-scale (100 patents). Considering the vastness of the patent database and realistic exploration at a large- scale, it is important to consider how these computational analyses change with orders of magnitude more data. We present analysis of 1,000 random mechanical patents, comparing the ability of LSA to Latent Dirichlet Allocation (LDA) to categorize patents into meaningful groups. Resulting implications for large(r) scale data mining of patents for DbA support are detailed. Keywords: Design-by-analogy ! Patent Analysis ! Latent Semantic Analysis ! Latent Dirichlet Allocation ! Function-based Analogy 1 Introduction Exposure to appropriate analogies during early stage design has been shown to increase the novelty, quality, and originality of generated solutions to a given engineering design problem [1-4]. Finding appropriate analogies for a given design problem is the largest challenge to practical implementation of DbA. -
The Impact of COVID-19 Lockdown Restrictions on Dogs & Dog Owners in the UK
The impact of COVID-19 lockdown restrictions on dogs & dog owners in the UK 26th August 2020 Table of contents Executive summary 1 Introduction 2 Dog demographics 4 Gastrointestinal health 4 Dog owners 5 Owners’ bond with their dogs 5 Owners’ feelings about their dog during lockdown 6 Contingency planning 8 Management of dogs 9 Routine changes 9 Exercise 9 Walk location 9 On/off lead walking 9 Frequency of walking 9 Duration of walking 9 Meeting other dogs 9 House rules 9 Time left alone 10 Dog behaviour 12 Behaviour towards adults 12 Behaviour towards children 13 General observations 14 Reactivity 14 Attention seeking behaviour 14 Behaviour on walks 14 Separation-related behaviour 14 Behaviour when about to be left 14 Behaviour when left 14 Enrichment, games and training 16 Toys 17 Puppies: socialisation/habituation 18 Conclusions 19 Future work 20 Appendix 21 Dogs Trust 1 Executive summary Lifestyle changes ensued for many people across the United Kingdom Dog behaviour (UK) in the Spring of 2020 due to ‘lockdown’ restrictions imposed to • Dogs’ behaviour towards household members was reported curb the spread of a newly emerged virus, SARS-CoV-2, which caused by owners to have changed considerably during lockdown, a global pandemic of the disease known as COVID-19. with large increases seen in the proportion of dogs reported to display attention-seeking and ‘clingy’ behaviours. Compared with More than 6,000 dog owners living in the UK completed our online February, there was an 82% increase in the proportion of owners survey between the 4th – 12th May 2020 (the most restrictive phase of who reported that their dog whined or barked when someone the lockdown measures). -
Global Pandemic, Local Devastation: Frontline Efforts to Support the Most Vulnerable the Freedom Fund Is a Leader in the Global Movement to End Modern Slavery
Global pandemic, local devastation: Frontline efforts to support the most vulnerable The Freedom Fund is a leader in the global movement to end modern slavery. We identify and invest in the most effective frontline efforts to eradicate modern slavery in the countries and sectors where it is most prevalent. Partnering with visionary investors, governments, anti-slavery organisations and those at risk of exploitation, we tackle the systems that allow slavery to persist and thrive. Working together, we protect vulnerable populations, liberate and reintegrate those enslaved and prosecute those responsible. Contents 2 Executive summary 4 The impact of covid-19 8 Our emergency response at a glance 11 Updates by country 11 India 20 Nepal 23 Myanmar 26 Thailand 29 Ethiopia 31 Brazil 34 Conclusion 36 List of partners providing emergency assistance Cover image: Ginny Baumann, © Freedom Fund The Freedom Fund 1 Executive summary Covid-19 has had a devastating Across our program areas, we have witnessed the ‘clocks being turned back’ on many hard-won impact on those most vulnerable to improvements for labour rights, gender rights and child modern slavery. protection. In this life-or-death situation for millions of the most vulnerable people, governments and Around the world, communities already suffering businesses are diverting crucial resources away from from poverty and exploitation have borne the brunt social and ethical priorities. In some cases, this is the of the virus and its accompanying economic fallout. result of genuine limits on resources and bandwidth Lockdowns and the shuttering of factories have amidst the pandemic. In others, powerholders are pushed millions of families to the brink of starvation.