The inter-bank market network models are constructed based on the inter-bank credit lending relationships, and the network efficiency characters of the Chinese inter-bank market are studied. Since it is impossible to ...The inter-bank market network models are constructed based on the inter-bank credit lending relationships, and the network efficiency characters of the Chinese inter-bank market are studied. Since it is impossible to obtain the specific credit data among banks, this paper estimates the inter-bank lending matrix based on the partial information of banks. Thus, directed network models of the Chinese inter-bank market are constructed by using the threshold method. The network efficiency measures and the effects of random attacks and selective attacks on the global efficiency of the inter-bank network are analyzed based on the network models of the inter-bank market. Empirical results suggest that the efficiency measures are sensitive to the threshold, and that the global efficiency is little affected by random attacks, while it is highly sensitive to selective attacks. Properties such as inter-bank market network efficiency would be useful for risk management and stability of the inter-bank market.展开更多
Stocks that are fundamentally connected with each other tend to move together.Considering such common trends is believed to benefit stock movement forecasting tasks.However,such signals are not trivial to model becaus...Stocks that are fundamentally connected with each other tend to move together.Considering such common trends is believed to benefit stock movement forecasting tasks.However,such signals are not trivial to model because the connections among stocks are not physically presented and need to be estimated from volatile data.Motivated by this observation,we propose a framework that incorporates the inter-connection of firms to forecast stock prices.To effectively utilize a large set of fundamental features,we further design a novel pipeline.First,we use variational autoencoder(VAE)to reduce the dimension of stock fundamental information and then cluster stocks into a graph structure(fundamentally clustering).Second,a hybrid model of graph convolutional network and long-short term memory network(GCN-LSTM)with an adjacency graph matrix(learnt from VAE)is proposed for graph-structured stock market forecasting.Experiments on minute-level U.S.stock market data demonstrate that our model effectively captures both spatial and temporal signals and achieves superior improvement over baseline methods.The proposed model is promising for other applications in which there is a possible but hidden spatial dependency to improve time-series prediction.展开更多
To examine the interdependency and evolution of Pakistan’s stock market,we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange(KSE-100)index.Using the ...To examine the interdependency and evolution of Pakistan’s stock market,we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange(KSE-100)index.Using the minimum spanning tree network-based method,we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan.Our results reveal a star-like structure after the general elections of 2018 and before those in 2008,and a tree-like structure otherwise.We also highlight key nodes,the presence of different clusters,and compare the differences between the three elections.Additionally,the sectorial centrality measures reveal economic expansion in three industrial sectors—cement,oil and gas,and fertilizers.Moreover,a strong overall intermediary role of the fertilizer sector is observed.The results indicate a structural change in the stock market network due to general elections.Consequently,through this analysis,policy makers can focus on monitoring key nodes around general elections to estimate stock market stability,while local and international investors can form optimal diversification strategies.展开更多
For effectively early warning the marketing risk caused along with the varied environment, a BP neural network method was introduced on the basis of analyzing the shortcomings of the risk early warning method, and com...For effectively early warning the marketing risk caused along with the varied environment, a BP neural network method was introduced on the basis of analyzing the shortcomings of the risk early warning method, and combined with the practical conditions of dairy enterprises, the index system caused by the marketing risk was also studied. The＇principal component method was used for screening the indexes, the grades and critical values of the marketing risk were determined. Through the configuration of BP network, node processing and error analysis, the early warning resuits of the marketing risk were obtained. The results indicate that BP neural network method can be effectively applied through the function approach in the marketing early warning with incomplete information and complex varied conditions.展开更多
Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock prices.The stock price data represents a financial time series data which becomes more difficult to predict due to its ...Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock prices.The stock price data represents a financial time series data which becomes more difficult to predict due to its characteristics and dynamic nature.Case description:Support Vector Machines(SVM)and Artificial Neural Networks(ANN)are widely used for prediction of stock prices and its movements.Every algorithm has its way of learning patterns and then predicting.Artificial Neural Network(ANN)is a popular method which also incorporate technical analysis for making predictions in financial markets.Discussion and evaluation:Most common techniques used in the forecasting of financial time series are Support Vector Machine(SVM),Support Vector Regression(SVR)and Back Propagation Neural Network(BPNN).In this article,we use neural networks based on three different learning algorithms,i.e.,Levenberg-Marquardt,Scaled Conjugate Gradient and Bayesian Regularization for stock market prediction based on tick data as well as 15-min data of an Indian company and their results compared.Conclusion:All three algorithms provide an accuracy of 99.9%using tick data.The accuracy over 15-min dataset drops to 96.2%,97.0%and 98.9%for LM,SCG and Bayesian Regularization respectively which is significantly poor in comparison with that of results obtained using tick data.展开更多
In this paper, we theoretically analyze the transformation of marketing strategy and the countermeasures under the network economic times. Network marketing is based on the network technology, including the whole proc...In this paper, we theoretically analyze the transformation of marketing strategy and the countermeasures under the network economic times. Network marketing is based on the network technology, including the whole process of marketing activities as a new form of marketing. In this paper, we analyze the issue from the listed perspectives. （1） Ultra space-and-time. The traditional marketing has very strong boundedness to the region, and this boundedness displays, the specifi c transaction can only be closed in the specific region, if the enterprise wants to expand the market share, only then establishes the retailing organization. （2） Interactivity. Network as a media, with the one-on-one interaction, this feature allows companies to basic communicate with consumers, and strengthen consumer participation, to determine the product form, function and the price. （3） The symmetry of information. Consumers can fi nd all kinds of that related products on the Internet information, there are plenty of time to judge the various products and prices. Companies will also be released in a timely manner on the Internet the company’s latest product information. Under this basis, we propose the new idea on the network marketing development direction that will help to build up the more efficient marketing system.展开更多
With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and en...With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.展开更多
With the rapid development of Things of Internet and its related technologies such as Wireless Sensor Network and remote access system development, its application on agricultural and farming domain has become a new r...With the rapid development of Things of Internet and its related technologies such as Wireless Sensor Network and remote access system development, its application on agricultural and farming domain has become a new research direction. This paper discusses a practical and efficient system by applying mobile software development technologies and ZigBee communication network. To achieve a compact and flexible iOS-based client, this study takes advantage of Model-View-ViewModel pattern as well as Client/Server style. Several encryption technologies such as Message Digest algorithm and Rivest Shamir Adleman algorithm are combined to ensure information security. Compared to the common portable marketing system, the proposed system also provides accurate growth information which is collected by wireless sensor network, and proposes a more flexible design pattern for mobile client hence obtaining a better performance on iOS devices.展开更多
In a globalized world, not only the business market is overlapped but also marketing models take shape within economic systems. While there has been a proliferation in the implementation of marketing in the private se...In a globalized world, not only the business market is overlapped but also marketing models take shape within economic systems. While there has been a proliferation in the implementation of marketing in the private sector, this paper provides a useful entry point for the understanding role of marketing within the nonprofit sector focused on China, the second worldwide economic power. A number of senior managers and directors from different Non-Governmental Organizations （NGOs） were interviewed of what they understood marketing to be and how they considered and implemented marketing within organizational strategy. The findings showed that while marketing was identified as an interesting and influential concept, Chinese nonprofit managers generally had a limited understanding of a marketing theory. The article further discusses reasons behind the dynamic based on personalized networks of influence used and the potential implications for nonprofit entities in China, a sector that plays a very noteworthy role in transformative economies.展开更多
The paper introduced the connotation of network marketing of fresh agricultural products and analyzed the fundaments of launching the C2C marketing of fresh agricultural products in China.The fundaments mainly cover t...The paper introduced the connotation of network marketing of fresh agricultural products and analyzed the fundaments of launching the C2C marketing of fresh agricultural products in China.The fundaments mainly cover the development of e-commerce,the transformation of consumption concept,the change of life style and the features of Chinese agricultural production.The developmental status of the C2C marketing of Chinese fresh vegetables and fresh fruits is introduced and the plights,including imperfect rural network infrastructure,inadequate talents specialized in network marketing of fresh agricultural products,uneven quality of agricultural products,immature logistics system,uncertainty existed in faced by the C2C marketing of fresh agricultural products and imperfect governmental protection system,are pointed out.In the end,the developmental trend of Chinese network marketing of fresh agricultural products on the basis of C2C mode is described.展开更多
In this paper, the authors present a method to construct a simulation experiment system which used to prove how social network affects the stock market. The authors construct a model considered of three main stock mar...In this paper, the authors present a method to construct a simulation experiment system which used to prove how social network affects the stock market. The authors construct a model considered of three main stock market effect factors： cognitive factors, social factors and economic factors. In the simulation system, free-scale social network is generated for information relations among investors in stock market. The authors simulate the organization information propaganda processes and generate stock related news. The generated news contains economy factors and sudden events. Stockholders cooperate with the related stockholders in their social network, and make stock exchange decision based on this news and their cognitive understanding of this news. Simulation results shows that the social network news propaganda effect stock prices. If social network in stock market have circles, the news affection will be amplified.展开更多
This work examines the role of social network sites as a tool used by companies to achieve marketing goals. As known from the main business literature, the social network represents one of the most important instrumen...This work examines the role of social network sites as a tool used by companies to achieve marketing goals. As known from the main business literature, the social network represents one of the most important instrument to improve the company fame by strengthening the affection of customers to the brand. For this reason, some companies use these tools to build relations and contacts with customers all over the world. The population of social networks users is made, for the most parts, of youngsters （people belonging to the 13-30 years old cluster）. In the last years, with the social web networking, social communication lost the exclusive social meaning and social network sites become strategic instruments for the construction of powerful relations that connect people with people and people with firms. This work is aimed at clarifying the genesis and the evolution of the relations between companies and potential customers, focusing on the tools used by the firm to achieve their marketing goals through social network sites （SNSs）. First of all, the work proposes the recognition of some studies about the origin of web social network and their links with marketing strategies. Secondly, it considers marketing goals achieved from any companies through social networking with a particular focus on advertising through web social networking.展开更多
Stock Market is the market for security where organized issuance and trading of Stocks take place either through exchange or over the counter in electronic or physical form. It plays an important role in canalizing ca...Stock Market is the market for security where organized issuance and trading of Stocks take place either through exchange or over the counter in electronic or physical form. It plays an important role in canalizing capital from the investors to the business houses, which consequently leads to the availability of funds for business expansion. In this paper, we investigate to predict the daily excess returns of Bombay Stock Exchange (BSE) indices over the respective Treasury bill rate returns. Initially, we prove that the excess return time series do not fluctuate randomly. We are applying the prediction models of Autoregressive feed forward Artificial Neural Networks (ANN) to predict the excess return time series using lagged value. For the Artificial Neural Networks model using a Genetic Algorithm is constructed to choose the optimal topology. This paper examines the feasibility of the prediction task and provides evidence that the markets are not fluctuating randomly and finally, to apply the most suitable prediction model and measure their efficiency.展开更多
With the rapid development of the Internet, market has been increasingly competitive and competition means are various. Internet Marketing has become a new way for enterprises to grow. Data mining of enterprise networ...With the rapid development of the Internet, market has been increasingly competitive and competition means are various. Internet Marketing has become a new way for enterprises to grow. Data mining of enterprise network marketing has become the new darling of many business managers.The marketing data will become a key to develop a corporate marketing strategy as an important basis tool. However, many companies now make mistakes in marketing data. They can＇t fully exploit the marketing data.lt can affect the development of enterprise network marketing strategy. This paper is based on the concept of marketing data and outline the importance of data mining for network marketing, then analyze a significant impact on the entemrise network marketin~ strate^w made by marketinR data mininR.展开更多
Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility ...Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility in accordance with its users＇ demand. In this paper, the authors proposed a method to analyze trait of users in market areas near stations by analyzing location based social network. After the datum collection from geotagged tweets, these GPS （global positioning system） datum were plotted to map attained from yahoo open location platform. Then the morphological analysis and terminology extraction system extracted the keywords and their scores. After calculating the distance from stations and users＇ GPS coordination, the authors extracted the array of keywords and corresponding scores in some station market area. Lastly, ratios of all users＇ scores and city＇s scores were calculated to examine the locality. Full combination of data collection, natural language processing and visualization enabled the authors to envisage distribution of collective background in city.展开更多
In the application process of the Internet and network marketing, many Chinese companies are actively engaged in practice, and after an exploratory period of time, companies accumulated some experience in a representa...In the application process of the Internet and network marketing, many Chinese companies are actively engaged in practice, and after an exploratory period of time, companies accumulated some experience in a representative model. Such as： Chinese companies have a combination with traditional marketing and purchase advanced software model and then implemented through secondary development, they also change management ideas and systems, etc. These experiences and models can provide an effective and common reference for enterprise＇ s development of China＇ s e-commerce.展开更多
ZTE Corporation,a leading global provider of telecommunications equipment and network solutions,announced on July 30,2009 that it has been ranked as the second largest global CDMA network supplier with 25%
With the rapid development of China＇s reform and opening up and the socialist market economy, the development of Internet technology has promoted the prosperity of e-commerce, and further promoted the rapid developme...With the rapid development of China＇s reform and opening up and the socialist market economy, the development of Internet technology has promoted the prosperity of e-commerce, and further promoted the rapid development of China＇s economy. Data mining technology is an advanced science and technology, which has important implications for the e-commerce data processing. Through the summary of the data mining technology, this article puts forward the application of data mining technology in electronic commerce, in order to better promote the development of electronic commerce.展开更多
Based on the text of posing on the network forum, the authors establish a set of keyword dictionary to measure the long and short investors＇ sentiment effectively, then they investigate the mutual relations between i...Based on the text of posing on the network forum, the authors establish a set of keyword dictionary to measure the long and short investors＇ sentiment effectively, then they investigate the mutual relations between investor sentiment and the trading market through a Multivariable BEKK-GARCH model of abnormal long and short investor sentiment, returns, and abnormal trading volume. The results show that abnormal sentiment of long investor has a negative impact on the returns and a positive impact on the abnormal trading volume; while abnormal sentiment of short investor has no impact on the return and a negative impact on the abnormal trading volume. Otherwise, there is the negative volatility effect from abnormal sentiment of long investor to returns and abnormal trading volume, the positive volatility effects from abnormal sentiment of short investor to returns, and no volatility effects from abnormal sentiment of short investor to abnormal trading volume. In addition, network forum investor sentiment is a factor affecting the trading market. The analysis of forum information plays a certain role in presenting market risk and improving efficiency in making investment decision.展开更多
基金The National Natural Science Foundation of China (No.70671025)the Scientific Research Foundation of Graduate School of Southeast University (No.YBJJ1014)
文摘The inter-bank market network models are constructed based on the inter-bank credit lending relationships, and the network efficiency characters of the Chinese inter-bank market are studied. Since it is impossible to obtain the specific credit data among banks, this paper estimates the inter-bank lending matrix based on the partial information of banks. Thus, directed network models of the Chinese inter-bank market are constructed by using the threshold method. The network efficiency measures and the effects of random attacks and selective attacks on the global efficiency of the inter-bank network are analyzed based on the network models of the inter-bank market. Empirical results suggest that the efficiency measures are sensitive to the threshold, and that the global efficiency is little affected by random attacks, while it is highly sensitive to selective attacks. Properties such as inter-bank market network efficiency would be useful for risk management and stability of the inter-bank market.
文摘Stocks that are fundamentally connected with each other tend to move together.Considering such common trends is believed to benefit stock movement forecasting tasks.However,such signals are not trivial to model because the connections among stocks are not physically presented and need to be estimated from volatile data.Motivated by this observation,we propose a framework that incorporates the inter-connection of firms to forecast stock prices.To effectively utilize a large set of fundamental features,we further design a novel pipeline.First,we use variational autoencoder(VAE)to reduce the dimension of stock fundamental information and then cluster stocks into a graph structure(fundamentally clustering).Second,a hybrid model of graph convolutional network and long-short term memory network(GCN-LSTM)with an adjacency graph matrix(learnt from VAE)is proposed for graph-structured stock market forecasting.Experiments on minute-level U.S.stock market data demonstrate that our model effectively captures both spatial and temporal signals and achieves superior improvement over baseline methods.The proposed model is promising for other applications in which there is a possible but hidden spatial dependency to improve time-series prediction.
文摘To examine the interdependency and evolution of Pakistan’s stock market,we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange(KSE-100)index.Using the minimum spanning tree network-based method,we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan.Our results reveal a star-like structure after the general elections of 2018 and before those in 2008,and a tree-like structure otherwise.We also highlight key nodes,the presence of different clusters,and compare the differences between the three elections.Additionally,the sectorial centrality measures reveal economic expansion in three industrial sectors—cement,oil and gas,and fertilizers.Moreover,a strong overall intermediary role of the fertilizer sector is observed.The results indicate a structural change in the stock market network due to general elections.Consequently,through this analysis,policy makers can focus on monitoring key nodes around general elections to estimate stock market stability,while local and international investors can form optimal diversification strategies.
文摘For effectively early warning the marketing risk caused along with the varied environment, a BP neural network method was introduced on the basis of analyzing the shortcomings of the risk early warning method, and combined with the practical conditions of dairy enterprises, the index system caused by the marketing risk was also studied. The＇principal component method was used for screening the indexes, the grades and critical values of the marketing risk were determined. Through the configuration of BP network, node processing and error analysis, the early warning resuits of the marketing risk were obtained. The results indicate that BP neural network method can be effectively applied through the function approach in the marketing early warning with incomplete information and complex varied conditions.
文摘Introduction:Nowadays,the most significant challenges in the stock market is to predict the stock prices.The stock price data represents a financial time series data which becomes more difficult to predict due to its characteristics and dynamic nature.Case description:Support Vector Machines(SVM)and Artificial Neural Networks(ANN)are widely used for prediction of stock prices and its movements.Every algorithm has its way of learning patterns and then predicting.Artificial Neural Network(ANN)is a popular method which also incorporate technical analysis for making predictions in financial markets.Discussion and evaluation:Most common techniques used in the forecasting of financial time series are Support Vector Machine(SVM),Support Vector Regression(SVR)and Back Propagation Neural Network(BPNN).In this article,we use neural networks based on three different learning algorithms,i.e.,Levenberg-Marquardt,Scaled Conjugate Gradient and Bayesian Regularization for stock market prediction based on tick data as well as 15-min data of an Indian company and their results compared.Conclusion:All three algorithms provide an accuracy of 99.9%using tick data.The accuracy over 15-min dataset drops to 96.2%,97.0%and 98.9%for LM,SCG and Bayesian Regularization respectively which is significantly poor in comparison with that of results obtained using tick data.
文摘In this paper, we theoretically analyze the transformation of marketing strategy and the countermeasures under the network economic times. Network marketing is based on the network technology, including the whole process of marketing activities as a new form of marketing. In this paper, we analyze the issue from the listed perspectives. （1） Ultra space-and-time. The traditional marketing has very strong boundedness to the region, and this boundedness displays, the specifi c transaction can only be closed in the specific region, if the enterprise wants to expand the market share, only then establishes the retailing organization. （2） Interactivity. Network as a media, with the one-on-one interaction, this feature allows companies to basic communicate with consumers, and strengthen consumer participation, to determine the product form, function and the price. （3） The symmetry of information. Consumers can fi nd all kinds of that related products on the Internet information, there are plenty of time to judge the various products and prices. Companies will also be released in a timely manner on the Internet the company’s latest product information. Under this basis, we propose the new idea on the network marketing development direction that will help to build up the more efficient marketing system.
文摘With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.
文摘With the rapid development of Things of Internet and its related technologies such as Wireless Sensor Network and remote access system development, its application on agricultural and farming domain has become a new research direction. This paper discusses a practical and efficient system by applying mobile software development technologies and ZigBee communication network. To achieve a compact and flexible iOS-based client, this study takes advantage of Model-View-ViewModel pattern as well as Client/Server style. Several encryption technologies such as Message Digest algorithm and Rivest Shamir Adleman algorithm are combined to ensure information security. Compared to the common portable marketing system, the proposed system also provides accurate growth information which is collected by wireless sensor network, and proposes a more flexible design pattern for mobile client hence obtaining a better performance on iOS devices.
文摘In a globalized world, not only the business market is overlapped but also marketing models take shape within economic systems. While there has been a proliferation in the implementation of marketing in the private sector, this paper provides a useful entry point for the understanding role of marketing within the nonprofit sector focused on China, the second worldwide economic power. A number of senior managers and directors from different Non-Governmental Organizations （NGOs） were interviewed of what they understood marketing to be and how they considered and implemented marketing within organizational strategy. The findings showed that while marketing was identified as an interesting and influential concept, Chinese nonprofit managers generally had a limited understanding of a marketing theory. The article further discusses reasons behind the dynamic based on personalized networks of influence used and the potential implications for nonprofit entities in China, a sector that plays a very noteworthy role in transformative economies.
文摘The paper introduced the connotation of network marketing of fresh agricultural products and analyzed the fundaments of launching the C2C marketing of fresh agricultural products in China.The fundaments mainly cover the development of e-commerce,the transformation of consumption concept,the change of life style and the features of Chinese agricultural production.The developmental status of the C2C marketing of Chinese fresh vegetables and fresh fruits is introduced and the plights,including imperfect rural network infrastructure,inadequate talents specialized in network marketing of fresh agricultural products,uneven quality of agricultural products,immature logistics system,uncertainty existed in faced by the C2C marketing of fresh agricultural products and imperfect governmental protection system,are pointed out.In the end,the developmental trend of Chinese network marketing of fresh agricultural products on the basis of C2C mode is described.
文摘In this paper, the authors present a method to construct a simulation experiment system which used to prove how social network affects the stock market. The authors construct a model considered of three main stock market effect factors： cognitive factors, social factors and economic factors. In the simulation system, free-scale social network is generated for information relations among investors in stock market. The authors simulate the organization information propaganda processes and generate stock related news. The generated news contains economy factors and sudden events. Stockholders cooperate with the related stockholders in their social network, and make stock exchange decision based on this news and their cognitive understanding of this news. Simulation results shows that the social network news propaganda effect stock prices. If social network in stock market have circles, the news affection will be amplified.
文摘This work examines the role of social network sites as a tool used by companies to achieve marketing goals. As known from the main business literature, the social network represents one of the most important instrument to improve the company fame by strengthening the affection of customers to the brand. For this reason, some companies use these tools to build relations and contacts with customers all over the world. The population of social networks users is made, for the most parts, of youngsters （people belonging to the 13-30 years old cluster）. In the last years, with the social web networking, social communication lost the exclusive social meaning and social network sites become strategic instruments for the construction of powerful relations that connect people with people and people with firms. This work is aimed at clarifying the genesis and the evolution of the relations between companies and potential customers, focusing on the tools used by the firm to achieve their marketing goals through social network sites （SNSs）. First of all, the work proposes the recognition of some studies about the origin of web social network and their links with marketing strategies. Secondly, it considers marketing goals achieved from any companies through social networking with a particular focus on advertising through web social networking.
文摘Stock Market is the market for security where organized issuance and trading of Stocks take place either through exchange or over the counter in electronic or physical form. It plays an important role in canalizing capital from the investors to the business houses, which consequently leads to the availability of funds for business expansion. In this paper, we investigate to predict the daily excess returns of Bombay Stock Exchange (BSE) indices over the respective Treasury bill rate returns. Initially, we prove that the excess return time series do not fluctuate randomly. We are applying the prediction models of Autoregressive feed forward Artificial Neural Networks (ANN) to predict the excess return time series using lagged value. For the Artificial Neural Networks model using a Genetic Algorithm is constructed to choose the optimal topology. This paper examines the feasibility of the prediction task and provides evidence that the markets are not fluctuating randomly and finally, to apply the most suitable prediction model and measure their efficiency.
文摘With the rapid development of the Internet, market has been increasingly competitive and competition means are various. Internet Marketing has become a new way for enterprises to grow. Data mining of enterprise network marketing has become the new darling of many business managers.The marketing data will become a key to develop a corporate marketing strategy as an important basis tool. However, many companies now make mistakes in marketing data. They can＇t fully exploit the marketing data.lt can affect the development of enterprise network marketing strategy. This paper is based on the concept of marketing data and outline the importance of data mining for network marketing, then analyze a significant impact on the entemrise network marketin~ strate^w made by marketinR data mininR.
文摘Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility in accordance with its users＇ demand. In this paper, the authors proposed a method to analyze trait of users in market areas near stations by analyzing location based social network. After the datum collection from geotagged tweets, these GPS （global positioning system） datum were plotted to map attained from yahoo open location platform. Then the morphological analysis and terminology extraction system extracted the keywords and their scores. After calculating the distance from stations and users＇ GPS coordination, the authors extracted the array of keywords and corresponding scores in some station market area. Lastly, ratios of all users＇ scores and city＇s scores were calculated to examine the locality. Full combination of data collection, natural language processing and visualization enabled the authors to envisage distribution of collective background in city.
文摘In the application process of the Internet and network marketing, many Chinese companies are actively engaged in practice, and after an exploratory period of time, companies accumulated some experience in a representative model. Such as： Chinese companies have a combination with traditional marketing and purchase advanced software model and then implemented through secondary development, they also change management ideas and systems, etc. These experiences and models can provide an effective and common reference for enterprise＇ s development of China＇ s e-commerce.
文摘ZTE Corporation,a leading global provider of telecommunications equipment and network solutions,announced on July 30,2009 that it has been ranked as the second largest global CDMA network supplier with 25%
文摘With the rapid development of China＇s reform and opening up and the socialist market economy, the development of Internet technology has promoted the prosperity of e-commerce, and further promoted the rapid development of China＇s economy. Data mining technology is an advanced science and technology, which has important implications for the e-commerce data processing. Through the summary of the data mining technology, this article puts forward the application of data mining technology in electronic commerce, in order to better promote the development of electronic commerce.
文摘Based on the text of posing on the network forum, the authors establish a set of keyword dictionary to measure the long and short investors＇ sentiment effectively, then they investigate the mutual relations between investor sentiment and the trading market through a Multivariable BEKK-GARCH model of abnormal long and short investor sentiment, returns, and abnormal trading volume. The results show that abnormal sentiment of long investor has a negative impact on the returns and a positive impact on the abnormal trading volume; while abnormal sentiment of short investor has no impact on the return and a negative impact on the abnormal trading volume. Otherwise, there is the negative volatility effect from abnormal sentiment of long investor to returns and abnormal trading volume, the positive volatility effects from abnormal sentiment of short investor to returns, and no volatility effects from abnormal sentiment of short investor to abnormal trading volume. In addition, network forum investor sentiment is a factor affecting the trading market. The analysis of forum information plays a certain role in presenting market risk and improving efficiency in making investment decision.
