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This paper aims to extract the comment targets in Chinese online shopping platform.

The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.

The extracting comment target method the authors proposed in this paper is effective.

First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.

Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.

The extracting comment target method the authors proposed in this paper is effective.

The study aims to present an agent-based simulation model (ABM) for exploring interorganizational coordination scenarios in local disaster preparedness. This approach includes local actors and logistical processes as agents to compare various strategic coordination mechanisms.

The ABM model, developed in the Latin American context, specifically focuses on a case study of Colombia. Three coordination mechanisms (centralized, decentralized and cluster-type) have been evaluated using three performance indicators: effectiveness, efficiency and flexibility.

Simulation results show that the decentralized scenario outperforms in terms of efficiency and flexibility. On the contrary, the centralized and cluster-type scenarios demonstrate higher effectiveness, achieving a greater percentage of requirements coverage during the disaster preparedness stage. The ABM approach effectively evaluates strategical coordination mechanisms based on the analyzed performance indicators.

This study has limitations due to the application of results to a single real case. In addition, the focus of the study is primarily on a specific type of disaster, specifically hydrometeorological events such as flash floods, torrential rains and landslides. Moreover, the scope of decision-making is restricted to key actors involved in local-level disaster management within a municipality.

The proposed ABM model has the potential as a decision-making tool for policies and local coordination schemes for future disasters. The simulation tool could also explore diverse geographical scenarios and disaster types, demonstrating its versatility and broader applicability for further insights and recommendations.

This study examined the influence of information and communication technology (ICT) on Nigeria's trade in sectors. Specifically, the research evaluated the effects of internet penetration, mobile phone subscriptions and fixed telephone subscriptions on exports and imports.

The study considered data from 1995 to 2022, highlighting ten trade sectors per standard international trade classification (SITC) single digit. It utilised the panel auto-regressive distributed lag (ARDL) with a preference for a pooled mean group (PMG) estimator.

The study finds that, in the short run, increases in internet penetration, mobile phone subscriptions and fixed telephone subscriptions significantly decrease export levels in Nigeria. Nonetheless, ICT advancements, particularly in mobile and fixed telephone subscriptions, significantly boost import activities by 17.9 and 41.5% in the long run, highlighting their positive impact on trade dynamics. In the long run, mobile telephone subscriptions substantially negatively affect exports. In contrast, internet penetration and fixed telephone subscriptions show no significant impact, indicating differing influences of ICT components on trade over time.

The study underscored the need to prioritise enhancing ICT infrastructure to boost export growth, especially in sectors identified under the SITC framework. Strategies should be developed to mitigate the negative impacts associated with ICT advancements.

The study used the SITC framework, which presents different export and import sectors. It offers a distinctive examination of the short- and long-term effects of ICT on Nigeria's trade sectors. It also provided valuable insights into the impact of mobile and internet technologies on exports and imports, highlighting sector-specific effects and the need for strategic resource allocation.

The shipper selects a suitable shipping route and plans for a voyage in order to import and export cargo on the basis of published sailing schedules. The reliability of the sailing schedule will influence the shipper’s logistics expense, which means that the logistics costs will depend on the reliability of schedules published by container shipping companies. Therefore, it is important to consider factors which can cause delays would for container ships sailing on sea routes. The reliability of published sailing schedules can be affected by a number of different factors. This study adopts the multi-criteria decision making (MCDM) method to estimate the importance of the delaying factors in a sailing schedule. In addition, the consistent fuzzy preference relations (CFPR) method is applied to identify the subjective importance (weights) of the delaying factors. The entropy weight method combined with the actual performance of the container shipping company are both used when estimating the objective importance (weights) of the delaying factors. According to the analysis results, the criteria can be divided into four quadrants with different management implications, which indicate that instructions for chase strategy, sailing schedule control, fleet allocation, transship operation arrangement and planning for ports in routes are often ignored by container shipping companies. Container shipping companies should consider adjusting their operational strategies, which would greatly improve their operational performance.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

Guided by stimulus-organism-response (SOR) theory, this study analyzed the user-generated content (UGC) produced by attendees from six anime conventions in the USA.

A total of 739 online reviews and 1,932 photos were collected from the social platforms of six large anime conventions in the USA (Yelp and Facebook), and the study employed thematic analysis and image analysis to analyze the collected UGCs.

The findings revealed eight main themes (i.e. ambient and space, customers, service and products, sign and symbol, social density, emotional status, motivation, and behavior intention) and 32 subthemes across the three dimensions of SOR theory. Leveraging the power of cutting-edge image analysis, the image labels obtained from the analysis contributed to the creation of network clusters. The result of the image analysis also continued consistently with the thematic analysis result, which reflected SOR theory.

Theoretically, the study applied SOR theory and blended thematic and image analyses to gain a comprehensive understanding of anime convention attendees’ experience and categorized the attendees’ emotional status as positive or negative to reflect their overall evaluation. Practically, this study highlighted some complaints from attendees and provided suggestions for operators. However, the study focused only on large anime conventions in the USA; future studies should compare attendees’ experiences with small and large conventions or anime conventions worldwide.

The study utilized UGCs to understand the key patterns essential to attendees during anime conventions in the USA and applied SOR theory to its investigation.

Because of the expansion of the internet and Web 2.0 phenomenon, new challenges are emerging in the disclosure practises adopted by organisations in the public-sector. This study aims to examine local governments’ (LGOs) use of social media (SM) in disclosing environmental actions/plans/information as a new way to improve accountability to citizens to obtain organisational legitimacy and the related sentiment of citizens’ judgements.

This paper analyses the content of 39 Italian LGOs’ public pages on Facebook. After the distinction between five classes of environmental issues (air, water, energy, waste and territory), an initial study is performed to detect possible sub-topics applying latent Dirichlet allocation. Having a list of posts related to specific environmental themes, the researchers computed the sentiment of citizens’ comments. To measure sentiment, two different approaches were implemented: one based on a lexicon dictionary and the other based on convolutional neural networks.

Facebook is used by LGOs to disclose environmental issues, focussing on their main interest in obtaining organisational legitimacy, and the analysis shows an increasing impact of Web 2.0 in the direct interaction of LGOs with citizens. On the other hand, there is a clear divergence of interest on environmental topics between LGOs and citizens in a dialogic accountability framework.

Sentiment analysis (SA) could be used by politicians, but also by managers/entrepreneurs in the business sector, to analyse stakeholders’ judgements of their communications/actions and plans on corporate social responsibility. This tool gives a result on time (i.e. not months or years after, as for the reporting system). It is cheaper than a survey and allows a first “photograph” of stakeholders’ sentiment. It can also be a useful tool for supporting, developing and improving environmental reporting.

To the best of the authors’ knowledge, this paper is one of the first to apply SA to environmental disclosure via SM in the public sphere. The study links modern techniques in natural language processing and machine learning with the important aspects of environmental communication between LGOs and citizens.