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Sentiment analysis technologies have a strong impact on financial markets. In recent years there has been increasing interest in analyzing the sentiment of investors. The objective of this paper is to evaluate the current state of the art and synthesize the published literature related to the financial sentiment analysis, especially in investor sentiment for prediction of stock price. Starting from this overview the paper provides answers to the questions about how and to what extent research on investor sentiment analysis and stock price trend forecasting in the financial markets has developed and which tools are used for these purposes remains largely unexplored. This paper represents the comprehensive literature-based study on the fields of the investors sentiment analytics and machine learning applied to analyzing the sentiment of investors and its influencing stock market and predicting stock price.

To what extent is students' understanding of computer science culturally situated? This, possibly philosophical question, has come to the surface at Uppsala University, Uppsala, Sweden, where many Chinese students study computer science together with the local students. We did an exploratory study using email interviews to see if our intuitions could be relied on. We collected data from Chinese students studying in master programs and analysed the data using a phenomenographic perspective. A complex intertwined relationship between the content of their learning (the WHAT), the ways in which they went about studying (the HOW), the aims of their studies (the WHY), and the competencies developed from the intercultural context they studied in (the WHERE) was observed. In this paper we offer some insights from the results of the pilot study and discuss how they have shaped our on-going study in the field.

Investor sentiment and emotions have a strong impact on financial markets. In recent years there has been increasing interest in analyzing the sentiment of investors for stock price prediction using machine learning. Existing prediction models mostly depend on the analysis of trading data and company profit. few prediction theories have been built based on individual investors' sentiments. The fundamental reason is the difficulty to measure individual investors' sentiment.

Human resources are essential to the survival, success, and long-term growth of a company. Hotel is an industry requiring a high level of human resources for delivering high-quality personal service to the hotel guests to maintain its competitiveness in the business environment. With the rapid economic growth in Macao started in 2002, all the industries have been growing fast and competing fiercely for the limited manpower in Macao. However, the Macao hotel industry has been losing its attractiveness in the Macao labor market and needs to rely on non-local workers with a limited stay in Macao. The management team of the Macao hotel industry is looking for a solution to maintain a stable workforce. Therefore, a study has been conducted on the effectiveness of its employee retention strategies. A questionnaire was designed to collect the preferences of the employees and interviews were conducted to understand the perspective of the management team toward the employee retention strategies. The study shows the employee strategies are focused on key employees’ interests such as career development and prospect. However, the communication between the management team and employees failed and led to employee turnover.

Small and medium-sized enterprises (SMEs) can benefit significantly from open innovation by gaining access to a broader range of resources and expertise using absorptive capacitive, and increasing their visibility and reputation. Nevertheless, multiple barriers impact their capacity to absorb new technologies or adapt to develop them. This paper aims to perform an analysis of relevant topics and trends in Open Innovation (OI) and Absorptive Capacity (AC) in SMEs based on a bibliometric review identifying relevant authors and countries, and highlighting significant research themes and trends. The defined string query is submitted to the Web of Science database, and the bibliometric analysis using VOSviewer software. The results indicate that the number of scientific publications has consistently increased during the past decade, indicating a growing interest of the scientific community, reflecting the industry interest and possibly adoption of OI, considering Absorptive. This bibliometric analysis can provide insights on the most relevant regions the research areas are under intensive development.

The understanding of how people accept and embrace new policies is vital in today's world. This paper introduces an original way of looking at this by adapting the widely recognized Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2). The goal is to provide a foundational model for assessing policy acceptance. More specifically, we adapted the UTAUT-2 framework to study how Macau residents perceive the "Northbound Travel for Macau Vehicles" policy, which allows cars with Macau registration plates to enter China. Using structural equation modeling software (SmartPLS), we analyze data collected from 136 respondents who experienced the policy.Our findings reveal that Performance Expectancy (PE) and Habit (HB) significantly influence individuals' intention to take advantage of the policy. In other words, people are more likely to embrace policies they perceive as beneficial and that align with their existing habits. Effort Expectancy (EE) and Facilitating Conditions (FC) do not significantly impact acceptance, perhaps as a result of participants' familiarity with the policy and their resource availability. Surprisingly, while not directly tied to usage, Social Influence (SI) shows a high mean value, suggesting its potential role in policy acceptance when influential individuals adopt the policy. This pioneering research contributes to the field by bridging the gap between technology acceptance models and policy studies. Most importantly, it validates the use of the UTAUT-2 as a technology framework that is adapted for assessing policy acceptance.

Stock price prediction has always been challenging due to its volatility and unpredictability. This paper performs a preliminary exploratory comparison that utilizes Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) algorithms to forecast the stock market in Hong Kong. It considers a public dataset publicly available and uses feature engineering to extract relevant features. Then, LSTM and SVM algorithms are applied to predict stock prices. Our results show that the proposed machine learning techniques can predict stock prices in Hong Kong's share market with the error metrics presented, and, for this purpose, LSTM achieved better results than SVM, with MSE = 0.0026, RMSE = 0.0508, MAE = 0.0406, and MAPE = 1.325.

It has been proven in numerous research that mindfulness can be helpful to reduce stress and chronic pain (Hall, 2014; Lindström, n.d.; Tong et al., 2015). While interactive mindfulness has been one of the focuses in the recent mobile applications market, usually tackling three essential human senses: audio, visual, and touch, each mobile application has quite some different approaches in terms of interactivity. Some focus on the touch and visual, and some on audio (environmental sounds or instructing meditation). Immersing oneself in virtual reality (VR) creates a constant stream of interactivity. Nonetheless, what are the conditions for an (in)tangible virtual reality to be more effective? Under the COVID-19 pandemic and lockdown since the end of 2019, Macao has been facing a social concern that we cannot travel easily to visit our decedents’ graves abroad, let alone the existing concerns of expensive burial services, lack of space, and alternative burial options. Also, taking into consideration that standard funeral service in Macao is often too brief, and getting briefer, thus lacking the opportunity to properly farewell the decedent, this research is proposing a virtual reality 3D model construction of the Chapel of St. Michael, located in St. Michael the Archangel Cemetery in Macao, to be streamed on a 360 virtual tour platform, Kuula. co. By immersing in this virtual reality, the participant is to have a single user experience for mindfulness with the decedent. To ensure valid and reliable results that address the research aims and objectives, a single-user experiment is going to be set up with multiple electronic devices, namely, the smartphone iPhone X with cardboard VR, the tablet iPad Pro, and the Oculus Quest 2. The methodology to collect the data will be using observation and simulation. The experiment will be started with an introduction to the project and conducted with no instruction, allowing users to explore and examine all features in this immersive experience. Along with a post-experience survey (interview + questionnaire), we seek its conditions and impacts on Macao residents in terms of interactive mindfulness and participants’ expectation of testing, for the first time in Macao, a virtual reality grave mourning experience.

Among the multiple images used to promote Macao as a touristic destination, we can find some related with the Christian traditions, in particular with the Catholic devotions to the Passion of Christ and the cult of the Virgin Mary. Discussing the concept of “dangerous memory” as proposed by Johann Baptist Metz and analyzing the rituals associated with the devotions around the Passion of Jesus, this paper aims to look at, and present, the different perceptions of a message of subversion of unbalanced relations of power and domination, such as the image of the suffering Jesus in the contemporary society of Macau. The method followed in this paper is ethnographic and structured around some major contributions in the field of Ritual Studies. The implications of this research are related with the different perceptions and usages of a religious image and the drift of its power.

This paper introduces a concept proposal for accessing driving behavior in public transportation through Mobile Crowd Sensing (MCS), as part of a long-term research project on Advanced Public Transportation System (APTS). The proposed concept makes use of mobile device's accelerometer and passengers' qualitative evaluation to identify aggressive driving behavior, which is believed to be a major factor for unnecessary accidents and fuel consumption. A survey and comparison of IT services (mobile applications and websites) provided by Macau Government and private bus companies in Macau, regarding bus-related information, such as fares, routes and route diversions is also provided.