The study makes a contrastive analysis of the differences in the comments of people from different social status in their Mini-blogs.It aims to find the manifestations of those differences by analyzing the underlying ...The study makes a contrastive analysis of the differences in the comments of people from different social status in their Mini-blogs.It aims to find the manifestations of those differences by analyzing the underlying causes and provide constructive suggestions on how to build a more harmonious public platform,which is of its great significance.展开更多
With the rising and spreading of micro-blog, the sentiment classification of short texts has become a research hotspot. Some methods have been developed in the past decade. However, since the Chinese and English are d...With the rising and spreading of micro-blog, the sentiment classification of short texts has become a research hotspot. Some methods have been developed in the past decade. However, since the Chinese and English are different in language syntax, semantics and pragmatics, sentiment classification methods that are effective for English twitter may fail on Chinese micro-blog. In addition, the colloquialism and conciseness of short Chinese texts introduces additional challenges to sentiment classification. In this work, a novel hybrid learning model was proposed for sentiment classification of Chinese micro-blogs, which included two stages. In the first stage, emotional scores were calculated over the whole dataset by utilizing an improved Chinese-oriented sentiment dictionary classification method. Data with extremely high or low scores were directly labeled. In the second stage, the remaining data were labeled by using an integrated classification method based on sentiment dictionary, support vector machine(SVM) and k-nearest neighbor(KNN). An improved feature selection method was adopted to enhance the discriminative power of the selected features. The two-stage hybrid framework made the proposed method effective for sentiment classification of Chinese micro-blogs. Experiments on the COAE2014(Chinese Opinion Analysis Evaluation 2014) dataset show that the proposed method outperforms other schemes.展开更多
In this work, a rumor’s spreading and controlling in a directed Micro-blog user network being consisted with 580 000 nodes are simulated. By defining some authority nodes that release anti-rumor information as the pr...In this work, a rumor’s spreading and controlling in a directed Micro-blog user network being consisted with 580 000 nodes are simulated. By defining some authority nodes that release anti-rumor information as the prevention strategy, the effect of the nodes’ role in network on rumor’s suppression is studied. The findings show that rumor will be spread out fast and reach a stable level within limited steps. The suppression of rumor is more predominated by the intervening opportunity, the earlier the intervention strategy was implemented, the better the rumor’s controlling could be achieved. The controlling effect is less relevant with the role of the authority nodes in network.展开更多
After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group ...After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.展开更多
User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influenc...User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influence on the information multi-step communication in a micro-biog. The multi-steps of information communication are divided into first-step and non-first-step, and user influence is classified into five dimensions. Actual data from the Sina micro-blog is collected to construct the model by means of an approach based on structural equations that uses the Partial Least Squares （PLS） technique. Our experimental results indicate that the dimensions of the number of fans and their authority significantly impact the information of first-step conxrnunication. Leader rank has a positive impact on both first-step and non-first-step communication. Moreover, global centrality and weight of friends are positively related to the information non-first-step communication, but authority is found to have much less relation to it.展开更多
Taking Meteorological Knowledge official micro-blog ＂ Meteorological Knowledge＂ and Beijing Meteorological Bureau official micro-blog ＂ Meteorology Beijing＂ as the research objects,the differences of different typ...Taking Meteorological Knowledge official micro-blog ＂ Meteorological Knowledge＂ and Beijing Meteorological Bureau official micro-blog ＂ Meteorology Beijing＂ as the research objects,the differences of different types of meteorological government micro-blog and the contribution of each factor were analyzed by comparing changes of the number of fans,micro-blog comments and forwarding and other key elements during March1 to May 31 in 2012. The results showed that the number of fans was one of important indexes to determine the influence of meteorological government micro-blog,and the high active fans played a more prominent role. During the period of study,the fans number of ＂ Meteorology Beijing＂ was far more than ＂ Meteorological Knowledge＂,the daily micro-blog released number and comment forwarding number were both more than ＂ Meteorological knowledge＂,but the proportion of active fans of ＂ Meteorological knowledge＂ was larger than ＂ Meteorology Beijing＂. Timeliness was of greater contribution to advancing the meteorological government micro-blog influence. During the period of study,the proportions of comments and forwarding number of morning weather forecast were the largest,the evening weather forecast took the second place,and the noon was the smallest.But the influence of noon weather forecast micro-blog increased most highly approximately by 15% because of the higher timeliness. The content and form also made great contribution to the influence of meteorological government micro-blog. Comparison of different types of meteorological micro-blog showed that,the number of fans and the influence of meteorological government micro-blog which mainly published real-time meteorological information were larger than which mainly published meteorological popular science knowledge.展开更多
In order to improve the service level of the University Library and increase the utilization rate of the students' libraries, the domestic libraries began to use micro-blog and WeChat. The use of micro-blog and We...In order to improve the service level of the University Library and increase the utilization rate of the students' libraries, the domestic libraries began to use micro-blog and WeChat. The use of micro-blog and WeChat is in line with the characteristics of college students and can improve the service level of University libraries effectively. In this article, I will start with introducing micro- blog and WeChat, briefly describe the current situation of using micro-blog and WeChat in university libraries, and the measures to improve the service level of university libraries by using micro-blog and WeChat.展开更多
Personality prediction on social network has become a hot topic.At present,most studies are using single-task classification/regression machine learning.However,this method ignores the potential association between mu...Personality prediction on social network has become a hot topic.At present,most studies are using single-task classification/regression machine learning.However,this method ignores the potential association between multiple tasks.Also an ideal prediction result is difficult to achieve based on the small scale training data,since it is not easy to get a lot of social network data with personality label samples.In this paper,a robust multi-task learning method(RMTL)is proposed to predict Big-Five personality on Micro-blog.We aim to learn five tasks simultaneously by extracting and utilizing appropriate shared information among multiple tasks as well as identifying irrelevant tasks.For a set of Sina Micro-blog users’information and personality labeled data retrieved by questionnaire,we validate the RMTL method by comparing it with 4 single-task learning methods and the mere multi-task learning.Our experiment demonstrates that the proposed RMTL can improve the precision rate,recall rate of the prediction and F value.展开更多
Beijing Municipal Public Security Bureau and related departments have issued a regulation to strengthen the management of Twitter-like micro-blogs.The regulation,issued on December 16,2011,requires Internet companies ...Beijing Municipal Public Security Bureau and related departments have issued a regulation to strengthen the management of Twitter-like micro-blogs.The regulation,issued on December 16,2011,requires Internet companies registered in the city and offering micro-blogging services to have their users register with their real names and personal information.Users＇ identity information must be validated before they begin blogging.Starting March 16,2012,microbloggers without real-name registration will not be allowed to blog.展开更多
During the past few decades, time series analysis has become one popular method for solving stock forecasting problem. However, depending only on stock index series makes the performance of the forecast not good enoug...During the past few decades, time series analysis has become one popular method for solving stock forecasting problem. However, depending only on stock index series makes the performance of the forecast not good enough, because many external factors which may be involved are not taken into consideration. As a way to deal with it, sentiment analysis on online textual data of stock market can generate a lot of valuable information as a complement which can be named as external indicators. In this paper, a new method which combines the time series of external indicators and the time series of stock index is provided. A special text processing algorithm is proposed to obtain a weighted sentiment time series. In the experiment, we obtain financial micro-blogs from some famous portal websites in China. After that, each micro-blog is segmented and preprocessed, and then the sentiment value is calculated for each day. Finally, an NARX time series model combined with the weighted sentiment series is created to forecast the future value of Shanghai Stock Exchange Composite Index(SSECI).The experiment shows that the new model makes an improvement in terms of the accuracy.展开更多
Broadcasting short items on the Internet is emerging as a phenomenal trend On the evening of December 23, a post on the micro-blog of Hunan Communications Radio caught
The year 2010 is being called Year One for micro-blogging in China. More than 20 percent of the events that spread through the Internet in 2010 and attracted nationwide attention or global
文摘The study makes a contrastive analysis of the differences in the comments of people from different social status in their Mini-blogs.It aims to find the manifestations of those differences by analyzing the underlying causes and provide constructive suggestions on how to build a more harmonious public platform,which is of its great significance.
基金Projects(61573380,61303185)supported by the National Natural Science Foundation of ChinaProject(13BTQ052)supported by the National Social Science Foundation of China+1 种基金Project(2016M592450)supported by the China Postdoctoral Science FoundationProject(2016JJ4119)supported by the Hunan Provincial Natural Science Foundation of China
文摘With the rising and spreading of micro-blog, the sentiment classification of short texts has become a research hotspot. Some methods have been developed in the past decade. However, since the Chinese and English are different in language syntax, semantics and pragmatics, sentiment classification methods that are effective for English twitter may fail on Chinese micro-blog. In addition, the colloquialism and conciseness of short Chinese texts introduces additional challenges to sentiment classification. In this work, a novel hybrid learning model was proposed for sentiment classification of Chinese micro-blogs, which included two stages. In the first stage, emotional scores were calculated over the whole dataset by utilizing an improved Chinese-oriented sentiment dictionary classification method. Data with extremely high or low scores were directly labeled. In the second stage, the remaining data were labeled by using an integrated classification method based on sentiment dictionary, support vector machine(SVM) and k-nearest neighbor(KNN). An improved feature selection method was adopted to enhance the discriminative power of the selected features. The two-stage hybrid framework made the proposed method effective for sentiment classification of Chinese micro-blogs. Experiments on the COAE2014(Chinese Opinion Analysis Evaluation 2014) dataset show that the proposed method outperforms other schemes.
文摘In this work, a rumor’s spreading and controlling in a directed Micro-blog user network being consisted with 580 000 nodes are simulated. By defining some authority nodes that release anti-rumor information as the prevention strategy, the effect of the nodes’ role in network on rumor’s suppression is studied. The findings show that rumor will be spread out fast and reach a stable level within limited steps. The suppression of rumor is more predominated by the intervening opportunity, the earlier the intervention strategy was implemented, the better the rumor’s controlling could be achieved. The controlling effect is less relevant with the role of the authority nodes in network.
文摘After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.
基金supported by the National Natural Science Foundation of China(Grant No.60873246)China Information Technology Security Evaluation Center
文摘User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influence on the information multi-step communication in a micro-biog. The multi-steps of information communication are divided into first-step and non-first-step, and user influence is classified into five dimensions. Actual data from the Sina micro-blog is collected to construct the model by means of an approach based on structural equations that uses the Partial Least Squares （PLS） technique. Our experimental results indicate that the dimensions of the number of fans and their authority significantly impact the information of first-step conxrnunication. Leader rank has a positive impact on both first-step and non-first-step communication. Moreover, global centrality and weight of friends are positively related to the information non-first-step communication, but authority is found to have much less relation to it.
基金Supported by the Public Industry(Meteorology) Special Funds for Scientific Research Projects(GYHY201106037)
文摘Taking Meteorological Knowledge official micro-blog ＂ Meteorological Knowledge＂ and Beijing Meteorological Bureau official micro-blog ＂ Meteorology Beijing＂ as the research objects,the differences of different types of meteorological government micro-blog and the contribution of each factor were analyzed by comparing changes of the number of fans,micro-blog comments and forwarding and other key elements during March1 to May 31 in 2012. The results showed that the number of fans was one of important indexes to determine the influence of meteorological government micro-blog,and the high active fans played a more prominent role. During the period of study,the fans number of ＂ Meteorology Beijing＂ was far more than ＂ Meteorological Knowledge＂,the daily micro-blog released number and comment forwarding number were both more than ＂ Meteorological knowledge＂,but the proportion of active fans of ＂ Meteorological knowledge＂ was larger than ＂ Meteorology Beijing＂. Timeliness was of greater contribution to advancing the meteorological government micro-blog influence. During the period of study,the proportions of comments and forwarding number of morning weather forecast were the largest,the evening weather forecast took the second place,and the noon was the smallest.But the influence of noon weather forecast micro-blog increased most highly approximately by 15% because of the higher timeliness. The content and form also made great contribution to the influence of meteorological government micro-blog. Comparison of different types of meteorological micro-blog showed that,the number of fans and the influence of meteorological government micro-blog which mainly published real-time meteorological information were larger than which mainly published meteorological popular science knowledge.
文摘In order to improve the service level of the University Library and increase the utilization rate of the students' libraries, the domestic libraries began to use micro-blog and WeChat. The use of micro-blog and WeChat is in line with the characteristics of college students and can improve the service level of University libraries effectively. In this article, I will start with introducing micro- blog and WeChat, briefly describe the current situation of using micro-blog and WeChat in university libraries, and the measures to improve the service level of university libraries by using micro-blog and WeChat.
文摘Personality prediction on social network has become a hot topic.At present,most studies are using single-task classification/regression machine learning.However,this method ignores the potential association between multiple tasks.Also an ideal prediction result is difficult to achieve based on the small scale training data,since it is not easy to get a lot of social network data with personality label samples.In this paper,a robust multi-task learning method(RMTL)is proposed to predict Big-Five personality on Micro-blog.We aim to learn five tasks simultaneously by extracting and utilizing appropriate shared information among multiple tasks as well as identifying irrelevant tasks.For a set of Sina Micro-blog users’information and personality labeled data retrieved by questionnaire,we validate the RMTL method by comparing it with 4 single-task learning methods and the mere multi-task learning.Our experiment demonstrates that the proposed RMTL can improve the precision rate,recall rate of the prediction and F value.
文摘Beijing Municipal Public Security Bureau and related departments have issued a regulation to strengthen the management of Twitter-like micro-blogs.The regulation,issued on December 16,2011,requires Internet companies registered in the city and offering micro-blogging services to have their users register with their real names and personal information.Users＇ identity information must be validated before they begin blogging.Starting March 16,2012,microbloggers without real-name registration will not be allowed to blog.
基金the National Natural Science Foundation of China(No.61375053)
文摘During the past few decades, time series analysis has become one popular method for solving stock forecasting problem. However, depending only on stock index series makes the performance of the forecast not good enough, because many external factors which may be involved are not taken into consideration. As a way to deal with it, sentiment analysis on online textual data of stock market can generate a lot of valuable information as a complement which can be named as external indicators. In this paper, a new method which combines the time series of external indicators and the time series of stock index is provided. A special text processing algorithm is proposed to obtain a weighted sentiment time series. In the experiment, we obtain financial micro-blogs from some famous portal websites in China. After that, each micro-blog is segmented and preprocessed, and then the sentiment value is calculated for each day. Finally, an NARX time series model combined with the weighted sentiment series is created to forecast the future value of Shanghai Stock Exchange Composite Index(SSECI).The experiment shows that the new model makes an improvement in terms of the accuracy.
文摘Broadcasting short items on the Internet is emerging as a phenomenal trend On the evening of December 23, a post on the micro-blog of Hunan Communications Radio caught
文摘The year 2010 is being called Year One for micro-blogging in China. More than 20 percent of the events that spread through the Internet in 2010 and attracted nationwide attention or global
