In this article, we review the literature which proposes attacker-defender games to protect against strategic adversarial threats. More specifically, we follow the systematic literature review methodology to collect and review 127 journal articles that have been published over the past 15 years. We start by briefly discussing the common application areas that are addressed in the literature, although our focus in this review lies heavily in the approaches that have been adopted to model and solve attacker-defender games. In studying these approaches, we begin by analyzing the following features of the proposed game formulations: the sequence of moves, number of players, nature of decision variables and objective functions, and time horizons. We then analyze the common assumptions of perfect rationality, risk neutrality, and complete information that are enforced within the majority of the articles, and report on state-of-the-art research which has begun relaxing these assumptions. We find that relaxing these assumptions presents further challenges, such as enforcing new assumptions regarding how uncertainties are modeled, and issues with intractability when models are reformulated to account for considerations such as risk preferences. Finally, we examine the methods that have been adopted to solve attacker-defender games. We find that the majority of the articles obtain closed-form solutions to their models, while there are also many articles that developed novel solution algorithms and heuristics. Upon synthesizing and analyzing the literature, we expose open questions in the field, and present promising future research directions that can advance current knowledge.

Take-away food (also referred to as “take-out” food in different regions of the world) is a very convenient and popular dining choice for millions of people. In this article, we collect online textual data regarding “take-away food safety” from Sina Weibo between 2015 and 2018 using the Octopus Collector. After the posts from Sina Weibo were preprocessed, users’ emotions and opinions were analyzed using natural language processing. To our knowledge, little work has studied public opinions regarding take-away food safety. This paper fills this gap by using latent Dirichlet allocation (LDA) and k-means to extract and cluster topics from the posts, allowing for the users’ emotions and related opinions to be mined and analyzed. The results of this research are as follows: (1) data analysis showed that the degree of topics have increased over the years, and there are a variety of topics about take-away food safety; (2) emotional analysis showed that 93.8% of the posts were positive; and (3) topic analysis showed that the topic of public discussion is diverse and rich. Our analysis of public opinion on take-away food safety generates insights for government and industry stakeholders to promote the healthy and vigorous development of the food industry.

Over recent years, food safety has garnered widespread attention and concern from society. Concurrently, social media sites and online forums have become popular platforms to disseminate news, share opinions, and connect with one’s social network. In this research, we focus on the intersection of food safety and online social networking by utilizing natural language processing techniques and social network analysis to study public opinions related to food safety. Using real data collected from a popular Chinese question-and-answer platform, we first identify hot topics related to food safety, and then analyze the emotional state of users in each community (i.e., users communicating about the same topic) to understand the public’s sentiment related to different food safety topics. We proceed by forming semantic networks to analyze the characteristics of food safety opinion networks. Our results show that Internet users form modular communities, each with differences in topics of concern and emotional states of community users. Users focus on a wide range of topics, showing that overall, food safety awareness is increasing. This paper provides novel insights that can help interested stakeholders monitor the discussions and opinions related to food safety.