Number Of Microblogs Research Articles

Microblog publicity and IPO underpricing

ABSTRACT Based on many cases of publicity using social media in the market, this paper empirically examines the damage of microblog publicity to market efficiency by using the sample of IPO companies. The results show that the companies posting microblogs during the IPO publicity period have higher IPO underpricing, and the more the number of microblogs, the richer the content, the higher the proportion of microblogs in the operating activities, the higher the IPO underpricing. These relationships are stronger in the enterprises with higher degree of information asymmetry and management valuing social media more. Furthermore, microblogs posted during the IPO period mainly influence investor sentiment, especially small investors. In addition, the short-term stock market performance of the companies posting microblogs is significantly worse. This paper provides a theoretical basis for standardizing the information disclosure behavior of listed companies using social media.

Microblog publicity and IPO underpricing

ABSTRACT Based on many cases of publicity using social media in the market, this paper empirically examines the damage of microblog publicity to market efficiency by using the sample of IPO companies. The results show that the companies posting microblogs during the IPO publicity period have higher IPO underpricing, and the more the number of microblogs, the richer the content, the higher the proportion of microblogs in the operating activities, the higher the IPO underpricing. These relationships are stronger in the enterprises with higher degree of information asymmetry and management valuing social media more. Furthermore, microblogs posted during the IPO period mainly influence investor sentiment, especially small investors. In addition, the short-term stock market performance of the companies posting microblogs is significantly worse. This paper provides a theoretical basis for standardizing the information disclosure behavior of listed companies using social media.

Research on Correlation of Users′ Topic Interests and Topic Information Diffusion in Microblog Networks

The topic analysis on the Sina microblog data is studied by using the Twitter-LDA topic model. The analysis based on correlation of users' topic interests shows that topic interests between users follow the three degrees of correlation. Within the same topic interest when the number of microblogs that users publish increases, the number of microblogs that their fans within three degrees publish also increases in fluctuation, and the similarity of topic interests between users and their multi-degree fans decreases with the increase of degree. Through the analysis and comparison of the diffusion difference of diverse topic categories, we find that users prefer the information with lifestyle topic, reposting probability is significantly different among microblogs within different topic categories, and the average reposting count can be 10 times in difference. In microblog information diffusion trees, diffusion depth, diffusion time interval and users' diffusion ability all show different characteristics for microblogs with different topic categories.

Hot Topics on Microblog Based on Findings and Social Governance

In the finding of hot topics on microblog, the short text, less word, non-standard word use and other features of microblog have made the traditional identification method of hot topic powerless. To solve this problem, discovery method of microblog hot topic based on speed increase has been put forward. First, divide pretreated microblog according to windows with equal quality, count word frequency of each word in each window and express as two-tuple sequence of time; then calculate increase slope of each word in every two adjacent windows to find words with faster increasing speed; later calculate increasing speed of users and article number of microblogs related to the word to make sure whether the word is hot subject term; finally produce hot topic from the cluster of hot subject term. The feasibility of this method has been verified by experiment. Experimental results show that this method has improved identification efficiency and lowered omission ratio and fall-out ratio, which can effectively and promptly discover the hot topic of microblog.

Parallel Micro Blog Crawler Construction for Effective Opinion Leader Approximation

It is important to research and find out opinion leader in time of increased huge number of Micro Blog users around our world and daily life. Our governments in different countries around the world have found that it is a vital fact to analysis and control message spreading in Micro Blog and other social network. For the reason that opinion leaders always play vital role in information spreading in Micro Blog and it is necessary to detect opinion leaders precisely. In this article, we has constructed a SINA Micro Blog APIs based Micro Blog crawling and analysis tool. Furthermore, a novel MapReduce based Micro blog crawler and node betweenness approximation computation method was proposed better accuracy and less running time to detect core opinion leaders in Micro Blog graphs.

Estimating the diffusion models of crisis information in micro blog

The study tries to construct the diffusion models of crisis information in micro blog. We propose three information release patterns in micro blog according to the duration of crisis information released, namely concentrated release, continuous release, and pulse release. Based on Logistic function, three respective diffusion models are constructed. We choose three crisis events to test the diffusion models using the variables of the number of micro blogs with the crisis information (NMCI) and the increment of NMCI. The estimate results show that the diffusion of crisis information in micro blogs can be described by Logistic function, and the growth curve of NMCI is S-shaped.

Content Mining and Network Analysis of Microblog Spam

The number of microblogs’ user is growing rapidly with the increase of spam. Firstly, we give microblog a formal definition, and then divide spam into two types: news and advertisements. We collect 1,760,314 items of 188MB microblog news to complete the process of content mining. Using ROST Content Mining, we work on topology macro statistics, time series mining, and so on. We find that the group of microblog presents the feature of small world. Its coefficient with the same degree is negative and the probability of news microblog followers is 0.0002, while the rate of second spread is 0.011.We put forward a recursive filtering method to estimate the rate of spread on many occasions and we import cross-relation method that switches the node that are difficult for network analysis to easy forms and do social network analysis.