摘要：
Accurate wind speed forecasting is capable of increasing the stability of wind power system. Notably, there are numerous factors affecting wind speed, thus causing wind speed forecasting to be difficult. To address the above -mentioned challenge, a novel hybrid model integrating genetic algorithm (GA), variational mode decomposition (VMD), improved dung beetle optimization algorithm (IDBO), and Bidirectional long short-term memory network based on attention mechanism (BiLSTM-A) is proposed in this study to achieve satisfactory forecasting performance. In the proposed model, GA is adopted to optimize the VMD to eliminate noise and extract original series attributes. And the IDBO is adopted for hyperparameters selection for the BiLSTM-A. The proposed GA-VMD-IDBO-BiLSTM-A is compared with nine established comparable models, with the aim of verifying its forecasting performance. A series of experiments on four 1 -hour real wind series in Stratford are performed to assess the performance of the model. The MAPE of the four datasets forecasting results reached 1.4%, 2.4%, 3.5%, 2.4%. As indicated by the experimental results, GA-VMD can better process the data and improve the forecasting accuracy. IDBO can optimize the parameters of BiLSTM model and improve the forecasting performance. The dual -optimization wind speed forecasting model can obtain high accuracy and strong stability.
作者机构：
[Tian, Lingkun; Zhou, Zijuan; Zhang, J; Zhang, Jun] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Zhang, J; Zhang, Jun] Cent China Normal Univ, E Commerce Res Ctr Hubei Prov, Wuhan, Peoples R China.
通讯机构：
[Zhang, J ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;Cent China Normal Univ, E Commerce Res Ctr Hubei Prov, Wuhan, Peoples R China.
摘要：
The item and pod storage assignment problems, two critical issues at the strategic level in robotic mobile fulfillment systems, have a strong correlation and should be studied together. Moreover, the workload balance in each picking aisle needs to be considered in the storage assignment problems to avoid robots' congestion within picking aisles. Motivated by these, the joint optimization of item and pod storage assignment problems (J-IPSAP) with picking aisles' workload balance is studied. The mixed integer programming model of the J-IPSAP with the workload balance constraint is formulated to minimize the robots' movement distance. The improved genetic algorithm (IGA) with the decentralized pod storage assignment strategy is designed to solve the J-IPSAP model. The experimental results show that the IGA can obtain high-quality solutions when compared with Gurobi and the two-stage heuristic algorithms. The robots' movement distance is smallest when the width-to-length ratio of the storage area is close to 1, and the robots' movement distance will increase with more stringent workload balance constraints.
摘要：
With the proliferation of social media, the detection of fake news has become a critical issue that poses a significant threat to society. The dissemination of fake information can lead to social harm and damage the credibility of information. To address this issue, deep learning has emerged as a promising approach, especially with the development of Natural Language Processing (NLP). This study introduces a novel approach called Graph Global Attention Network with Memory (GANM) for detecting fake news. This approach leverages NLP techniques to encode nodes with news context and user content. It employs three graph convolutional networks to extract informative features from the news propagation network and aggregates endogenous and exogenous user information. This methodology aims to address the challenge of identifying fake news within the context of social media. Innovatively, the GANM combines two strategies. First, a novel global attention mechanism with memory is employed in the GANM to learn the structural homogeneity of news propagation networks, which is the attention mechanism of a single graph with a history of all graphs. Second, we design a module for partial key information learning aggregation to emphasize the acquisition of partial key information in the graph and merge node-level embeddings with graph-level embeddings into fine-grained joint information. Our proposed method provides a new direction in news detection research with a combination of global and partial information and achieves promising performance on real-world datasets.
期刊：
Environmental Science and Pollution Research,2024年31(12):18448-18464 ISSN：0944-1344
通讯作者：
Xu, SC
作者机构：
[Hao, Meng-Ge; Meng, Xiao-Na; Xu, SC; Xu, Shi-Chun] China Univ Min & Technol, Sch Econ & Management, Xuzhou 221116, Peoples R China.;[Xue, Xiao-Fei] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
通讯机构：
[Xu, SC ] C;China Univ Min & Technol, Sch Econ & Management, Xuzhou 221116, Peoples R China.
关键词：
Digital economy;Zero-waste city;Waste management;Industrial structure upgrading;Green technology innovation
摘要：
The digital economy is playing a crucial effect in the field of environmental governance. Digital and intelligent management is an essential means to fully realize the "zero-waste city" construction. The present paper investigates the impact of digital economy on China's provincial "zero-waste city" construction. The results indicate that digital economy can contribute to "zero-waste city" construction. The digital economy has a positive nonlinear effect on the construction of "zero-waste city," but the marginal effect is diminishing. The digital economy can facilitate "zero-waste city" construction by improving industrial structure upgrading and green technology innovation. Heterogeneity analysis reveals that digital economy contributes to the construction of "zero-waste city" in the eastern and western regions and high-level environmental regulation regions, while this impact is insignificant in the central region and low-level environmental regulation regions. The digital economy exerts the most significant positive influence on waste resource recycling followed by waste final disposal and then waste reduction at the source. These findings underscore the effect of digital economy in fostering "zero-waste city" construction and promoting sustainable waste management. The present study provides new ideas for the "zero-waste city" construction in emerging developing countries such as China.
作者机构：
[Li, Duantengchuan; Li, Bing; Xia, Tao] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China.;[Wang, Jing] Chongqing Univ Posts & Telecommun, Sch Automat, Chongqing 400065, Peoples R China.;[Shi, Fobo] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.;[Zhang, Qi; Zhang, Q] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Li, Bing] Hubei Luojia Lab, Wuhan 430079, Peoples R China.
通讯机构：
[Li, DTC; Li, B ] W;[Zhang, Q ] C;Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China.;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;Hubei Luojia Lab, Wuhan 430079, Peoples R China.
关键词：
Link prediction;Knowledge graph embedding;Shallow interaction;Deep interaction;Attention mechanism;Vector tokenization
摘要：
Inferring missing information from current facts in a knowledge graph (KG) is the target of the link prediction task. Currently, existing methods embed the entities and relations of KG as a whole into a low-dimensional vector space. Nonetheless, they ignore the multi-level interactions (shallow interactions, deep interactions) among the finer-grained sub-features of entities and relations. To overcome these limitations, we present a shallow-to-deep feature interaction for knowledge graph embedding (SDFormer). It takes into account the interpretability of sub-feature tokens of entities and relations and learns shallow-to-deep interaction information between entities and relations at a more fine-grained level. Specifically, entity and relation vectors are decomposed into sub-features to represent multi-dimensional information. Then, a shallow-to-deep feature interaction method is designed to capture multi-level interactions between entities and relations. This process enriches the feature representation by modeling the interaction between sub-features. Finally, a 1-X scoring function is utilized to calculate the score of each knowledge triplet. The experimental results on several benchmark datasets show that SDFormer obtains competitive performance results and more efficient training efficiency on other comparative models and because of the shallow-to-deep feature interaction between entities and relations.
摘要：
This paper explores the knowledge network structure of foreign research literature by applying the qualitative comparative analysis (QCA) method to the field of information science and library science (ISLS) from the perspective of the cocitation of social network actors such as authors, institutions, countries, and literature, and it further reveals the future application trends of this method. [Method/process] Based on 86 journals in the ISLS field that were downloaded from the Web of Science using the QCA method, the social network analysis (SNA) method and the visual analysis tool Gephi are used to analyse the author cooperation network, the research institution cooperation network, the national cooperation network, the cocitation network, the cutting-edge trends, etc., of journal papers. The analysis shows that the QCA method covers a wide range within the field of ISLS, but the research topics involved in this field are not concentrated, and the author cooperation network has scale-free characteristics. The application of the QCA method is still dominant in European and American countries, and China, the USA, and Italy all play key roles in the national cooperation network. Finally, the institutional cooperation network has certain small group attributes.
摘要：
DIGITAL HEALTH, Volume 10, Issue , January-December 2024. <br/>ObjectivesCyberchondria is increasingly recognized as the dark side of digital health, given the pervasive use of the internet as a main source of health information in people's daily lives. While previous studies have identified many factors contributing to cyberchondria, there is a dearth of research on the impact of health-related advertisements. Therefore, this study adopts the stressor–strain–outcome (SSO) model to investigate how health-related advertising interference is directly and indirectly related to cyberchondria.MethodsTo empirically validate the proposed research model, we conducted an online survey with 437 internet users with medical information seeking experience in China. Structural equation modeling (SEM) was employed to analyze the survey data.ResultsOur findings revealed a positive, direct association between health-related advertising interference and cyberchondria. Meanwhile, advertising interference was positively related to both information overload and information irrelevance, with the former further predicting cyberchondria. Moreover, doctor–patient communication weakened the positive effect of information overload on cyberchondria.ConclusionsThe study not only theoretically contributes to the literature by theorizing the relationship between health-related advertising interference and cyberchondria but also practically underlines the pivotal role of effective doctor–patient communication in reducing the development of cyberchondria.
期刊：
Information Processing & Management,2024年61(3):103649 ISSN：0306-4573
通讯作者：
Chi, MM
作者机构：
[Xia, Lixin; Zhai, Shanshan] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Chi, Maomao; Chi, MM] China Univ Geosci, Sch Econ & Management, Wuhan 430078, Peoples R China.;[Chi, Maomao; Chi, MM] Wuhan Technol & Business Univ, Inst Digital Commerce, Wuhan 430065, Peoples R China.;[Li, Xuguang] Shandong Univ Technol, Sch Informat Management, Zibo 255000, Peoples R China.
通讯机构：
[Chi, MM ] C;China Univ Geosci, Sch Econ & Management, Wuhan 430078, Peoples R China.;Wuhan Technol & Business Univ, Inst Digital Commerce, Wuhan 430065, Peoples R China.
关键词：
Configuration perspective;National natural science foundation of China;Youth program;Library and information science
摘要：
While extensive research has delved into various facets of science funding outputs and the determinants of funding approval, prevailing methodologies predominantly rely on descriptive statistics or regression analyses. These approaches often miss a holistic view that integrates the interplay of multiple influential factors. In this study, we leverage the scientific research productivity model to introduce the Institution-Capability-Demographics framework, encompassing three pivotal dimensions: institutional characteristics, individual capabilities, and individual demographics. Adopting a configuration perspective, we scrutinize the synergistic effects of these dimensions on the time-to-win in science funding applications. Our empirical analysis draws from data of 72 young scholars affiliated with the Youth Program for Library and Information Science (LIS) of the NSFC, all of whom secured funding between 2003 and 2019. Through the fuzzy-set qualitative comparative analysis (fsQCA), this study delineates four distinct mechanisms that expedite the application process for the NSFC's Youth Program: demographic-capability-institution synergy, capability-centric balance, demographic-capability harmony, and capability-institution equilibrium. The findings elucidate the intricate interdependencies of factors influencing the time-to-win in science funding, offering valuable guidance for science fund managers and fostering the growth of emerging scholars.
作者机构：
[Yang, Honglin] Hunan Univ, Sch Business Adm, Changsha 410082, Hunan, Peoples R China.;[Gao, Mingyun] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Xiao, Qinzi] Wuhan Inst Technol, Sch Management, Wuhan 430205, Peoples R China.
通讯机构：
[Mingyun Gao] S;School of Information Management, Central China Normal University, Wuhan, People’s Republic of China
关键词：
Grey forecasting;Grey power model;Generalized fractional-order accumulation;Derivation forms
摘要：
Considering the effective service life of products, this study initially defined a generalized fractional-order accumulation generation matrix covering the effective accumulation percentage. We suggested a generalized fractional-order accumulation grey power model (GFAGMP(1,1) model) using this matrix, along with its parameter estimate, error analysis, and time response function solution. We studied transformation and the link from the generalized GM(1,1) model to GFAGMP(1,1) model on the basis of integral and power function transformation and deduced three derivation forms of this model and their application range via the class ratio analysis. Finally, different forecasting models were compared with the actual sales data of Chinese refrigerators. The results of comparison demonstrated the feasibility and effectiveness of the GFAGMP(1,1) model in forecasting the home-appliance supply chain demand in China.
作者机构：
[Wang, Xuelin; Meng, Hua; Lu, Xinyuan] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Lu, Xinyuan] Cent China Normal Univ, Hubei Ecommerce Res Ctr, Wuhan 430079, Peoples R China.
通讯机构：
[Meng, H ] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
关键词：
Open innovation community (OIC);implicit contract;knowledge contribution;user behavior;network position;structural holes;network centrality
摘要：
Open innovation communities (OICs) have been expanding the scope of enterprises’ innovation activities, and their effective functioning hinges on the ongoing knowledge contributions from users. However, the research on the impact of contractual governance mechanisms on users’ knowledge-contribution behaviors has yet to be further explored. In this study, we provide a comprehensive definition of implicit contracts in OICs, clarify their dimensions, investigate their impact on users’ knowledge contribution, and explore how users’ network positions moderate these effects. Subsequently, we employ a questionnaire survey combined with web crawling to collect user data and empirically test the theoretical hypotheses. The results demonstrate that both user-user implicit contracts (i.e., user reciprocity, user trust, and user recognition) and user-community implicit contracts (i.e., community incentives, community trust, and community support) significantly and positively affect user knowledge contribution. Furthermore, users’ structural holes exert a significant positive moderating effect on these relationships. Notably, the moderating effect of network centrality is only significant in the influence of user-community implicit contracts, and not significant in the relationship between user-user implicit contracts and user knowledge contribution. The insights derived from this study offer valuable practical guidance for effectively operating and managing OICs.
摘要：
To reduce the conceptual ambiguity in interdisciplinary knowledge organization systems (KOSs) and enhance interdisciplinary KOS management, this paper proposes a framework for interdisciplinary semantic drift (ISD) detection based on the normal cloud model (NCM). In this framework, we first analyze the features of interdisciplinary concepts and propose a novel interdisciplinary concept extraction method based on cross-discipline statistical information. Secondly, the high-performance knowledge representation model NCM is adopted to represent each interdisciplinary concept with uncertainty, and then a new ISD degree calculation method is proposed based on the similarity cloud algorithm. Thirdly, to identify the direction of ISD after the degree calculation, we propose an ISD direction identification method according to the theory of knowledge potential energy (KPE). Fourthly, based on the above procedure, we propose an ISD detection algorithm to identify and visualize the ISD process. Finally, we evaluate the proposed framework on the concept of "information entropy" and compare the performance with three baselines. Experimental results demonstrate that our framework outperforms[ all the baselines, and the result is comparable to experts' judgments (0.808 on Spearman correlation, p<0.001). The research indicates the meaning of an interdisciplinary concept will drift from the high KPE discipline to the low KPE discipline as long as interdisciplinary knowledge potential differences (KPD) exist between these two related disciplines. We further identify three key factors that affect the degree of ISD: the length of the discipline chain of an interdisciplinary concept transfer, the number of source disciplines that an interdisciplinary concept comes from, and the knowledge distance between the source discipline and the target discipline. & COPY; 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access
作者机构：
[Tian, Lingkun; Zhou, Zijuan; Wang, Ping; Zhang, Jun; Zhang, Ning] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Wang, Ping; Zhang, Jun] Cent China Normal Univ, Ecommerce Res Ctr Hubei Prov, Wuhan, Peoples R China.
通讯机构：
[Jun Zhang] S;School of Information Management, Central China Normal University, Wuhan, China<&wdkj&>E-commerce Research Center of Hubei Province, Central China Normal University, Wuhan, China
关键词：
Bi-objective optimization problem;Energy expenditure;Human-robot coordinated;Multi-objective evolutionary algorithms;Robotic mobile fulfilment system;Storage assignment problem
作者机构：
[Liu, Rui; Liu, R; Yao, Xinjing; Wang, Yujun] Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.;[Liu, Chang] Chinese Acad Med Sci, Inst Med Plant Dev, Beijing, Peoples R China.
通讯机构：
[Liu, R ; Liu, C ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.;Chinese Acad Med Sci, Inst Med Plant Dev, Beijing, Peoples R China.
摘要：
A DNA barcode is a short piece of standard DNA sequence used for species determination and discrimination. Representation of DNA barcodes is essential for DNA barcodes' applications in the transportation and recognition of biological materials. Previously, we have compared different strategies for representing the DNA barcodes. In the present study, we have developed a compression algorithm based on binary coding or Huffman coding scheme, followed by converting the binary digits into Base64 digits. The combination of this compression algorithm and the QR representation leads to the dynamic DNA QR coding algorithm (DDQR). We tested the DDQR algorithm on simulated data and real DNA barcode sequences from the commonly used plant and animal DNA barcode markers: rbcL, matK, trnH-psbA, ITS2, and COI. We compared the compression efficiency of DDQR and another state-of-the-art DNA compression algorithm GeCo3 for sequences with various base compositions and lengths. We found that DDQR had a higher compression rate than GeCo3 for DNA sequences shorter than 800 bp, which is the typical size range for DNA barcodes. We also upgraded a web server (http://www.1kmpg.cn/ddqr) that provides three functions: retrieval of DNA barcode sequences, encoding DNA barcode sequences to DDQR codes, and decoding DDQR codes to DNA barcode sequences. The DDQR algorithm and the webserver will be invaluable to applying DNA barcode technology in the food and traditional medicine industries.
作者：
Zhang, Min;Zhang, Dongxin;Zhang, Yin;Yeager, Kristin;Fields, Taylor N.
期刊：
Journal of Informetrics,2023年17(4) ISSN：1751-1577
通讯作者：
Zhang, Y
作者机构：
[Zhang, Min] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Zhang, Dongxin] Southwest Univ, Sch Comp & Informat Sci, Chongqing, Peoples R China.;[Zhang, Yin; Fields, Taylor N.; Zhang, Y] Kent State Univ, Sch Informat, Kent, OH 44242 USA.;[Yeager, Kristin] Kent State Univ, Univ Lib, Kent, OH USA.
通讯机构：
[Zhang, Y ] K;Kent State Univ, Sch Informat, Kent, OH 44242 USA.
摘要：
Influence plays a critical role in information communication, and the ubiquitous use of social media has made measuring influence on social media platforms a salient challenge. While previous studies have attempted to measure and investigate influence on Twitter, there is no consensus on its definition or relation to fundamental Twitter metrics. This study examined relationships between a composite influence measure of Twitter and fundamental social media metrics using a sample of tweets from a multi-year public campaign. Correlation analyses indicated that a user's number of followers had the strongest correlation with the composite measure. Principal components analysis was conducted for dimension reduction, and multiple regression analysis was performed using the resulting components. The findings revealed that a user's network was the most important predictor of the composite influence measure and that there was a negative relationship between campaign related activity and the composite measure. Implications of these findings are discussed. Overall, this study contributes to the understanding of and future efforts in the measurement of influence on social media.
作者：
Ye, Guanghui;Wang, Cancan;Wu, Chuan;Peng, Ze;Wei, Jinyu;...
期刊：
Journal of Informetrics,2023年17(3):101421 ISSN：1751-1577
通讯作者：
Wu, C
作者机构：
[Wu, Chuan; Peng, Ze; Wu, C; Tan, Qitao; Wu, Lanqi; Ye, Guanghui; Wei, Jinyu; Song, Xiaoying; Wang, Cancan] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
通讯机构：
[Wu, C ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.
关键词：
Research front detection;Research grant information;Evolution analysis;Health informatics
摘要：
Identifying research fronts is an essential aspect of promoting scientific development. Many re-searchers choose their research directions and topics by analyzing their field's current research fronts. Many previous researchers have used academic papers or patents to identify research fronts; however, this is potentially outdated and reduces the prospective value of the research front detection. Considering this, this work proposes adapted indicators to conduct research front topic detection based on research grant data, which aims to identify research front topics and fore-cast trends using path analysis. First, research topics were identified using topic modeling, and then the mapping relations from topics to both fund projects and cross-domain categories were built. Then, research front topics were detected by multi-dimensional measurements, and the evo-lution of research topics was analyzed using topic evolution visualization to predict development trends. Finally, the Brillouin index was used to measure the cross-domain degree. Our method was evaluated using a dataset from the field of health informatics and was shown to be effective in research front identification. We found that the proposed adapted indicators were informative in identifying the evolutional trends in the health informatics field. In addition, research grants with higher cross-domain degrees are more likely to receive a high amount of funding.
摘要：
BACKGROUND: The web-based health question-and-answer (Q&A) community has become the primary and handy way for people to access health information and knowledge directly. OBJECTIVE: The objective of our study is to investigate how content-related, context-related, and user-related variables influence the answerability and popularity of health-related posts based on a user-dynamic, social network, and topic-dynamic semantic network, respectively. METHODS: Full-scale data on health consultations were acquired from the Metafilter Q&A community. These variables were designed in terms of context, content, and contributors. Negative binomial regression models were used to examine the influence of these variables on the favorite and comment counts of a health-related post. RESULTS: A total of 18,099 post records were collected from a well-known Q&A community. The findings of this study include the following. Content-related variables have a strong impact on both the answerability and popularity of posts. Notably, sentiment values were positively related to favorite counts and negatively associated with comment counts. User-related variables significantly affected the answerability and popularity of posts. Specifically, participation intensity was positively related to comment count and negatively associated with favorite count. Sociability breadth only had a significant impact on comment count. Context-related variables have a more substantial influence on the popularity of posts than on their answerability. The topic diversity variable exhibits an inverse correlation with the comment count while manifesting a positive correlation with the favorite count. Nevertheless, topic intensity has a significant effect only on favorite count. CONCLUSIONS: The research results not only reveal the factors influencing the answerability and popularity of health-related posts, which can help them obtain high-quality answers more efficiently, but also provide a theoretical basis for platform operators to enhance user engagement within health Q&A communities.
作者机构：
[Liang, Han; Chen, Jincai] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan, Peoples R China.;[Chen, Jincai; Lu, Ping] Huazhong Univ Sci & Technol, Inst Nat & Math Sci, Wuhan, Peoples R China.;[Wang, Ruili; Liang, Han] Massey Univ, Inst Nat & Math Sci, Auckland, New Zealand.;[Zeng, Jiangfeng] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Zeng, Jiangfeng] Ctr Data Governance & Intelligent Decis Making Hub, Wuhan, Peoples R China.
通讯机构：
[Zeng, JF ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;Ctr Data Governance & Intelligent Decis Making Hub, Wuhan, Peoples R China.
关键词：
Audio-visual event localization;Dynamic fusion;Attention mechanism;Difference loss
期刊：
Information Processing & Management,2023年60(4):103348 ISSN：0306-4573
通讯作者：
Duantengchuan Li<&wdkj&>Yan Zhang
作者机构：
[Li, Zhifei; Zhang, Yan] Hubei Univ, Sch Comp Sci & Informat Engn, Wuhan 430062, Hubei, Peoples R China.;[Zhang, Qi] Cent China Normal Univ, Sch Informat Management, Wuhan 430072, Hubei, Peoples R China.;[Zhu, Fangfang] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Hubei, Peoples R China.;[Zheng, Chao; Li, Duantengchuan] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Hubei, Peoples R China.
通讯机构：
[Duantengchuan Li; Yan Zhang] S;School of Computer Science, Wuhan University, Wuhan, Hubei 430072, China<&wdkj&>School of Computer Science and Information Engineering, Hubei University, Wuhan, Hubei 430062, China
作者机构：
[Cao, Shiyang] Shanxi Univ Finance & Econ, Int Exchange & Cooperat Dept, Taiyuan, Peoples R China.;[Ma, Xiao] Zhongnan Univ Econ & Law, Sch Informat & Safety Engn, Wuhan, Peoples R China.;[Yi, Ming; Zeng, Jiangfeng] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Zeng, Jiangfeng] Ctr Data Governance & Intelligent Decis Making Hub, Wuhan, Peoples R China.
通讯机构：
[Zeng, JF ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;Ctr Data Governance & Intelligent Decis Making Hub, Wuhan, Peoples R China.
关键词：
Financial sentiment analysis;Fresh and hot opinions;Temporal modeling;Fresh-hot bilinear pooling
摘要：
Financial sentiment analysis aims to extract public opinion about an institution to help financial researchers make better decisions. To predict sentiment more accurately, it is necessary for models to improve their capability to capture long-term temporal information and support multi-user interaction. However, existing methods only analyze sentiment based on one comment from a user, which fails to fully exploit the latent emotions of the public, and they lack effective temporal modeling and interaction capabilities. In this paper, we analyze a company from two perspectives to alleviate the above issues: (1) the fresh opinions can reflect timely public attitudes towards a company, while (2) the hot opinions provide the most influential views. A comprehensive exploration of fresh and hot financial sentiment can help researchers make more accurate determinations. To this end, we propose a novel financial sentiment classification framework (FSCN), that can capture temporal information and interact with the opinions of users to make a more comprehensive decision. Our approach takes into account the inherent temporal dependencies in public opinions and combines both views of information to achieve an accurate classification of financial sentiment. Specifically, the FSCN contains (1) a multi-opinion extractor to filter and extract features from massively fresh and hot opinions, respectively. (2) a fresh-hot bilinear pooling (FHBP) module to effectively fuse fresh and hot features. Additionally, to verify the effectiveness of the proposed method, we crawl data from the Internet and create a real-world public opinion dataset that consists of 79,350 comments from 837 companies. Extensive experiments demonstrate that our framework achieves state-of-the-art results on this real-world dataset and is capable of providing reliable service in the financial system. Codes will be released at https://github.com/zjfgh2015/FSCN .
