Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp

Helpful online reviews could be utilized to create sustainable marketing strategies in the restaurant industry, which contributes to national sustainable economic development. This study, the main aspects (including food/taste, experience, location, and value) from 294,034 reviews on Yelp.com were extracted empirically using the Latent Dirichlet Allocation (LDA) and positive and negative sentiment were assigned to each extracted aspect. Positive sentiments were associated with food/taste, while negative sentiments were associated with value. This study further proves a robust classification algorithm based on Support Vector Machine (SVM) with a Fuzzy Domain Ontology (FDO) algorithm outperforms other traditional classification algorithms such as Naïve Bayes (MB) and SVM ontology in predicting the helpfulness of online reviews. This study enriches the literature on managerial aspects of sustainability by analyzing a large amount of plain text data that customers generated. The results of this study could be used as sustainable marketing strategy for review website developers to design sophisticated, intelligence review systems by enabling customers to sort and filter helpful reviews based on their preferences. The extracted aspects and their assigned sentiment could also help restaurateurs better understand how to meet diverse customers’ needs and maintain sustainable competitive advantages.
Transmission of shocks between Chinese financial market and oil market

PurposeThe purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period.Design/methodology/approachThis study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-movement variables. Finally, the authors examine the spillover effects by estimating the BEKK GARCH model.FindingsThe wavelet coherency results indicate a substantial co-movement between oil and Chinese stock markets in the periods of high volatility. BEKK GARCH model outcomes confirm this relation and report the noteworthy bidirectional transmission of volatility between oil market shocks and the Chinese investor’s sentiment, chiefly in the crisis period. These results support the behavioral theory of contagion and highlight that the Chinese investor’s sentiment is a channel through which shocks are transmitted between the oil and Chinese equity markets. Thus, these results are important for Chinese authorities that should monitor the investor’s sentiment to better control the interaction between financial and real markets.Originality/valueThis study makes three major contributions to the existing literature. First, it pays attention to the recent 2015 Chinese stock market bumble. Second, it has gone some way toward enhancing our understanding of the volatility spillover between the investor’s sentiment, investor’s sentiment variation, oil prices and stock market returns (variables of interest) during oil and stock market crises. Third, it uses the continuous wavelet decomposition technique since it reveals the linkage between variables of interest at different time horizons.
A multivariate regression approach for identification of SNPs importance in prostate cancer

ABSTRACT Nowadays, it is well-known that there are several genetic alterations that can be employed as genetic markers of prostate cancer (PCa). The use of single nucleotide polymorphism (SNP) is one of the most promising areas of research in cancer investigation. The aim of the present research is to study the influence of the pathways with the help of models such as recursive partitioning method, to detect the SNP of relevance, and consequently the detection of PCa. Data are retrieved from MCC-Spain database, selecting cases and controls as a heterogeneous group. Recursive partitioning method decision trees allow to prune off the splits that are supposed to be not of interest. Then, with the selected pathways, multivariate adaptive regression spline models are trained, and its performance is assessed in terms of the Area Under Curve (AUC) of the Receiver Operating Characteristics (ROC) curve. As a result, with performance tests for researchers that work with genetic datasets, a dimensional reduction and tuning of the parameters for the models are determined. In the case of our research, a total of 12 SNPs were found as the most relevant of the above-mentioned database for the PCa detection.
Effect of Shanxi pilot emission trading scheme on industrial soot and dust emissions: A synthetic control method

To launch the nationwide emission trading scheme, some provinces in China were approved to design their pilot work for emission trading scheme according to local circumstances. Shanxi Province is the only pilot area with provincial trading market for industrial soot and dust emissions. This paper investigates the effect of Shanxi Pilot emission trading scheme on industrial soot and dust emissions by using the synthetic control method. The idea behind the synthetic control approach is to construct a combination of comparison cities to approximate the emission paths that the cities in Shanxi would have experienced in the absence of the pilot emission trading scheme. We demonstrate that, following Shanxi Pilot emission trading scheme, industrial soot and dust emissions fell markedly in Taiyuan, Datong, and Linfen relative to the synthetic counterparts. The finding that emission trading scheme can help achieve emission reduction targets is shown to be robust to the reduction in the number of control units, placebo tests, and difference-in-differences estimation.
Media Portrayal of Migrant Workers, Immigration Law and Policy in New Zealand 2008 - 2017

2 Attestation of Authorship . 6 Acknowledgements . 7 Chapter 1: Introduction . 8 1.1 Research Rationale and Significance . 8 1.2 Policy changes . 10 1.3 Media content . 11 1.4 Structure of this Dissertation . 11 Chapter 2: Literature Review . 13 2.1 Policy Decision Making . 14 2.2 Migrants . 16 2.3 Perception and Attitudes . 19 2.4 Business Influence . 20 2.5 Media influence . 21 2.6 Conclusion . 24 Chapter 3: Overview of the New Zealand context . 25 3.1 Issues for New Zealand . 26 3.2 New Zealanders’ Attitudes . 27 3.3 New Zealand Policies . 28 3.4 Migrants Coming to New Zealand . 29 3.5 Political influence . 30 3.6 Migration trends . 30 3.7 Conclusion . 32 Chapter 4: Methodology . 33 4.1 Research Rationale and Significance . 33 4.2 Research Design . 33 4.3 Data Collection . 34 4.4 Analysis Part One: Policy Analysis . 36 4.5 Analysis Part Two: Thematic Analysis . 37 4.6 Conclusion . 42 Chapter 5: Findings . 43 5.1 Interpretative Policy Analysis . 43 5.1.1 Internal Administration Circulars (2008) . 44 5.1.2 Immigration Act 2009 and subsequent amendments in 2015 . 43 5.1.3 Essential Skills Visa (2017) . 47
The Mediatisation of MFAS: Diplomacy in the New Media Ecology

The proliferation of social media has had a profound impact on the practice of diplomacy; diplomats can bypass the press and communicate their messages directly to online audiences. Subsequently, ministries of foreign affairs (MFAS) are now mediatised; they produce media content, circulate content through social media and adopt media logics in their daily operations. Through a case study of the Israeli MFA during the 2014 Gaza War, this article explores the mediatisation of MFAS. It does so by analysing how the Israeli MFA crafted frames through which online audiences could understand the war and demonstrates that these frames evolved as the conflict unfolded. It then draws attention to the important way in which MFAS are now media actors through a statistical analysis, which demonstrates that the use of images in tweets increased engagement with the Israeli MFA’s frames. Finally, the article illustrates how these frames were used to legitimize Israel’s actions, and delegitimise those of Hamas.
Analysing slow growth of mobile money market in India using a market separation perspective

ABSTRACT Since the application of mobile technology for financial services can contribute to the economic development of developing countries, it is critical to examine the inhibitors to using mobile money service in countries like India, which have an exceptionally low uptake of this service. Mobile money service enables the customer to carry out financial transactions over a mobile phone without requiring them to own a bank account. By adopting a market separation perspective, this theory-driven, exploratory study proposes and tests a rare event logistic regression model for using mobile money services in India. The analysis of 45,036 responses shows that the ownership of a SIM card (temporal separation), income and ownership of a bank account (financial separations), awareness of mobile money services (information separation), age and gender (social separations), and location of residence (spatial separation) significantly inhibit the use of mobile money services. Implications are discussed at the end.
Web-based Just-In-Time Retrieval for Cultural Content

Digital content providers of cultural resources face the challenge of disseminating their content to interested users – either because users do not know the existence of resources or do not know the access points. We propose to apply just-intime retrieval mechanisms to bring the content to the users in a web-based scenario. Our first prototype is a Chrome extension which proposes Europeana content based on the current user context, i.e., the current web site. We think that our approach is promising for scenarios where users are not aware of available content and therefore can and do not explicitly state an information need.
A possibilistic framework for the detection of terrorism‐related Twitter communities in social media

Since the appearance of social networks, there was a historic increase of data. Unfortunately, terrorists are taking advantage of the easiness of accessing social networks and they have set up profiles to recruit, radicalize, and raise funds. Most of these profiles have pages that exist as well as new recruits to join the terrorist groups, see, and share information. Therefore, there is a potential need for detecting terrorist communities in social networks in order to search for key hints in posts that appear to promote the militants' cause. In order to remedy this problem, we first use a possibilistic‐clustering algorithm that allows more flexibility when assigning a social network profile to clusters (non‐terrorist, terrorist‐sympathizer, terrorist). Then, we introduce a new possibilistic flexible graph mining method to discover similar subgraphs by applying possibilistic similarity rather than using hard structural exact similarity. We experimentally show the efficiency of our possibilistic approach through a detailed process of tweets extract, semantic processing, and classification of the community detection.
The foreign policy of the Islamic Republic of Iran at 40. A discourse analyis.

Detta examensarbete utgar fran det outredda faktum att den Islamiska republiken Iran (IRI) har kunnat driva fram sin agenda for sjalvstandighet och suveranitet fran imperialistiskt och kolonialt arvda dominansstrukturer. Denna agenda som ar baserad pa en militant diskurs om motstand och fred har mojliggjort for IRI att exponentiellt vinna regionalt och internationellt inflytande trots sin brist pa militar och ekonomisk hard makt. Genom att tillampa diskursanalys (arkeologi och genealogi) pa huvudsakligen iranska primar kallor, t.ex. IRI:s konstitution och anforanden vid Forenta Nationernas generalforsamling (FNGA), syftar uppsats till att svara pa fragan: vilken ar den narrativa attraktionen av IRI:s utrikespolitiska diskurs, sasom den har presenterats vid FNGA:s oppningssessioner under de forsta 40 aren? Uppsatsen drar slutsatsen att IRI:s utrikespolitiska diskurs, inriktad pa statsbaserat motstand mot dominans, mynnar ut i ett narrativ med attraktionskraft vilket sammantaget skapar legitimitet och handlingsutrymme for IRI:s utrikespolitiska intressen. Genom en analys av IRI:s utrikespolitiska diskurs som grundar sig pa en lasning av IRI:s utrikespolitik inom och genom dess egen logik, avser uppsatsen att fylla ett gap i forskningen av IRI:s utrikespolitik genom en omfattande tillampning av primara iranska kallor.
Microfinance and poverty reduction: Evidence from Djibouti

Does access to microfinance improve household welfare? We seek the answer to this question using data on 2,060 borrower and non-borrower households based in six major urban centers of Djibouti. We construct a composite index of multi-dimensional poverty and carry out estimations using a number of econometric techniques. Our results show that neither access to micro-credit nor its ostensibly productive use is significantly associated with poverty regardless of the duration of time since the loan was acquired. This holds both for access to, and the amount of micro-credit obtained. The results raise doubts on the effectiveness of Djibouti’s microfinance programme.
Visualization and Interaction for Ontologies and Linked Data

Producing RDF documents has always been a tedious task. To make it easier, most approaches propose an abstraction like forms to produce the data. In this paper, we propose Shacled Turtle, a method and a tool to ease the editing of RDF documents with auto-completion, based on RDFS and/or SHACL schemas. We also describe an experiment with volunteers to evaluate the usefulness of the tool, and we discuss its results.
An Investigation of Cyber Loss Data and Its Links to Operational Risk

Cyber risk is one of the most challenging areas of risk, not only because it is relatively nascent but also because it remains an elusive moving target due to an ever-evolving threat landscape. A lack of structured data and the systemic implications of multifaceted impacts of overlapping risk frameworks are additional factors that make this risk difficult to quantify. As a starting point for overcoming this challenge, our paper considers a potential definition of this risk type, encompassing confidentiality, integrity and availability; the key components of a cyber-risk framework; a taxonomy to help establish a common framework for data collection to aid quantification; and the key quantification challenges. It then focuses on quantifying the direct financial and compensatory losses emanating from cyber risks. To help us carry this out, dimensional analysis is incorporated in the same manner as it has been applied to operational losses; this enables the identification of any similarities and/ or gross deviations between the profiles of cyber and non-cyber operational losses. In all, considering the limited amount of cyber data available, this analysis shows that: (1) a taxonomy for cyber risk that maps directly to operational risk might be a worthwhile exercise; (2) cyber loss data has a fundamental risk profile similar to that of non-cyber operational risk losses, with both following the same trend; and (3) the underlying risk profile related to cyber losses has not changed materially over time. These findings come with the added implications that: (1) mapping the taxonomies of cyber and operational risk against each other could be conducted more objectively; (2) operational risk modeling techniques that have been developed over the past decade or so could be used in the same way to assess the direct financial impact of cyber risk as a starting point; and (3) although there has been an increase in both the frequency and the severity of cyber losses over the past few years, there has not been a major paradigm shift in their fundamental risk profile over the same period of time.
Designing a Natural User Interface to Support Information Sharing among Co-Located Mobile Devices

Users of mobile devices share their information through various methods, which are supported by mobile devices. However, the information sharing process of these methods are typically redundant and sometimes tedious. This is because it may require the user to repeatedly perform a series of steps to share one or more selected files with another individual. The proliferation of mobile devices support new, more intuitive, and less complicated solutions to information sharing in the field of mobile computing. The aim of this paper is to present MotionShare, which is a NUI application that supports information sharing among co-located mobile devices. Unlike other existing systems, MotionShare’s distinguishing attribute is its inability of relying on additional and assisting technologies in determining the positions of devices. A primary example is using an external camera to determine device positioning in a spatial environment. An analytical evaluation investigated the accuracy of device positioning and gesture recognition, where the results were positive. The empirical evaluation investigated any usability issues. The results of the empirical evaluation showed high levels of user satisfaction and that participants preferred touch gestures to point gestures.
Causal Relationships between Energy Consumption, Economic Growth and CO2 Emission in Sub-Saharan: Evidence from Dynamic Simultaneous-Equations Models

The purpose of this study is to investigate the interrelationship between energy-CO2 emission-GDP for Sub-Saharan countries covering the period 2000-2012. To circumvent this issue we use dynamic simultaneous-equation. Our empirical findings show that there is a bidirectional causal relationship between energy consumption and economic growth. The results support also a bidirectional relationship between energy consumption and electricity consumption, but variables reflecting pollution affect negatively electricity consumption. As well the rise in economic growth increases the level of CO2 emissions and vice versa.
Exchange Rate and Interest Rate Disconnect: The Role of Capital Flows, Currency Risk and Default Risk

Using survey based measures of exchange rate expectations from a large set of advanced countries and emerging markets during 1996–2015, we document new facts on international arbitrage and exchange rate determination. We find that positive interest rate differentials imply expected depreciation as predicted by the no-arbitrage condition, however the expected depreciation is not enough to offset the interest rate differentials, leading to UIP deviations. To understand why there is not a full offset, we evaluate the response of each component of the UIP relation—that is the interest rate differential term and and exchange rate adjustment term—to changes in global risk and country fundamentals. This exercise reveals that, in short horizons (1-3 month), expected depreciation as a response to a given shock is large enough to offset most of the interest rate differentials, narrowing down the UIP deviations in general, and vanishing them in the advanced economies. In long horizons (12 month), this is not the case due to a combination of different factors in different countries. In advance countries, currency risk plays a key role, where in bad times (high global risk), currency depreciates more than the expectations, leading to larger deviations. In emerging markets, there is not enough movement in the exchange rate adjustment term. Capital outflows from emerging markets as a result of both higher global risk and worsening country fundamentals lead to larger interest rate differentials. Although there is an expected and actual depreciation as a result of such outflows, these are not enough to offset the interest rate differentials as the role played by the default risk is more important.
High Involvement and Ethical Consumption: A Study of the Environmentally Certified Home Purchase Decision

Sustainable and energy efficient (SEE) attributes in the housing market have become a focus in Canada. Similarly, understanding the consumer’s decision-making process of this high-involvement ethical product has become a burgeoning area for researchers. This study describes the development of the subject, highlighting the nature of the ethical decision-making process and how it relates to this known intention–behaviour gap. An observation, followed by two studies consisting of in-depth interviews with real estate agents and sales representatives (n = 15) and home purchasers/consumers (n = 15), were conducted. Transcriptions were analysed qualitatively with NVivo Pro 12 software (NVivo Pro 12, QSR International Pty Ltd, Melbourne, Australia). Inductive thematic analysis revealed two main driving themes: information and trust in seller/realtor. Attribute investment return uncertainty was identified as a theme that affects the strength of the relationship between purchase intention and behaviour, whereas the trust in seller/realtor speaks to how and why this effect occurs. The findings present relationships among the driving factors that were identified by realtors and consumers in the SEE housing market, as well as barriers (investment return uncertainty) that prevent consumers from purchasing high-involvement ethical products.
Surrogate-Assisted Evolutionary Framework for Data-Driven Dynamic Optimization

Recently, dynamic optimization has received much attention from the swarm and evolutionary computation community. However, few studies have investigated data-driven evolutionary dynamic optimization, and most algorithms for evolutionary dynamic optimization are based on analytical mathematical functions. In this paper, we investigate data-driven evolutionary dynamic optimization. First, we develop a surrogate-assisted evolutionary framework for solving data-driven dynamic optimization problems (DD-DOPs). Second, we employ a benchmark based on the typical dynamic optimization problems set in order to verify the performance of the proposed framework. The experimental results demonstrate that the proposed framework is effective for solving DD-DOPs.
Closer to election, more light: electricity supply and elections in a postconflict transition economy

ABSTRACT In our paper, we analyse the supply of electricity in conjunction with elections in Kosovo. The results confirm our hypotheses that before scheduled (regular) parliamentary elections, the supply of electricity increases significantly above usual levels, but that this is not the case for early (snap) elections. This paper contributes to the Political Business Cycle (PBC) literature in two ways. It provides additional evidence of incumbent manipulation of non-classical policy instruments before elections. The paper contributes also to the PBC debate by revealing different incumbent strategies in scheduled and early elections, respectively, thus highlighting the importance of distinguishing between these types of elections in PBC research.