SEMINAR TOPIC : COMPARING TWITTER ARCHIVES
In the past one decade, there has been an exponential surge in the online activity of people across the globe. The volume of posts that are made on the web every second runs into millions. To add to this, the rise of social media platforms has led to flooding to content on the internet.Social media is not just a platform where people talk to each other, but it has become very vast and serves many more purposes. It has become a medium where people Express their interests.Share their views.Share their displeasures.Compliment companies for good and poor services.So in this seminar paper, we are going to learn how we can analyze what people are posting on social networks (Twitter) to come up a great application which helps companies to understand about their customers.Although counts of tweets citing academic papers are used as an informal indicator of interest, little is known about who tweets academic papers and who uses Twitter to find scholarly information. Without knowing this, it is difficult to draw useful conclusions from a publication being frequently tweeted.This study surveyed 2 users that have tweeted journal articles to ask about their scholarly-related Twitter uses. Almost half of the respondents (45%) did not work in academia, despite the sample probably being biased towards academics.Twitter was used most by people with a social science or humanities background. People tend to leverage social ties on Twitter to find information rather than searching for relevant tweets. Twitter is used in academia to acquire and share real-time information and to develop connections with others.
Key words: Big data, data analysis, social media, Twitter.
Project 1: Comparing impact of cross site scripting attacks on various
Scripting languages and identifying the complete techniques for
SEMINAR : DISTRIBUTED DATABASE
Description : Distributed database technology is expected to have a significant impact on data processing in the upcoming years. With the introduction of commercial products, expectations are that distributed database management systems will by and large replace centralized ones within the next decade. In this paper, we reflect on the promises of distributed database technology, take stock of where we are, and discuss the issues that remain to be solved. We also present new research issues, such as distributed object-oriented systems, distributed knowledge bases, multiprocessor data servers, and distributed multi database systems, that arise with the introduction of new technology and the subsequent relaxation of some of the assumptions underlying current systems
- programming Languages : R,PYTHON
- Data : BIGDATA,CLOUD COMPUTING