I created this presentation to present my research work to the committee. My research was on extracting tweets and analyzing it with an previously created ontology model. The results of the ontology model will help in identifying the domain area of the problem for which use had shared negative sentiments on tweeter. This system along with the ontology model developed for Postal service domain. The next step in research will be to generate automated responses on twitter to the user who shares negative sentiments.
https://www.youtube.com/watch?v=nvlHJgRE3pU
Won ITAC Graduation Projects Competition, ITAC ID: GP2015.R10.75
A web application that analyze big volumes of product reviews, social networks posts and tweets related to a given product. Then, present these results of this big data analytical job in a user friendly, understandable, and easily interpreted manner that can be used by different customers for different purposes.
Technologies used:
1- Hadoop
2- Hadoop Streaming
3- R Statistical
4- PHP
5- Google Charts API
Twitter Sentiment Analysis Project Done using R.
In these Project we deal with the tweets database that are avaialble to us by the Twitter. We clean the tweets and break them out into tokens and than analysis each word using Bag of Word concept and than rate each word on the basis of the score wheter it is positive, negative and neutral.
We used Naive Baye's Classifier as our base.
The big data phenomenon has confirmed the achievement of data access transformation. Sentiment analysis (SA) is one of the most exploited area and used for profit-making purpose through business intelligence applications. This paper reviews the trends in SA and relates the growth in the area with the big data era.
I created this presentation to present my research work to the committee. My research was on extracting tweets and analyzing it with an previously created ontology model. The results of the ontology model will help in identifying the domain area of the problem for which use had shared negative sentiments on tweeter. This system along with the ontology model developed for Postal service domain. The next step in research will be to generate automated responses on twitter to the user who shares negative sentiments.
https://www.youtube.com/watch?v=nvlHJgRE3pU
Won ITAC Graduation Projects Competition, ITAC ID: GP2015.R10.75
A web application that analyze big volumes of product reviews, social networks posts and tweets related to a given product. Then, present these results of this big data analytical job in a user friendly, understandable, and easily interpreted manner that can be used by different customers for different purposes.
Technologies used:
1- Hadoop
2- Hadoop Streaming
3- R Statistical
4- PHP
5- Google Charts API
Twitter Sentiment Analysis Project Done using R.
In these Project we deal with the tweets database that are avaialble to us by the Twitter. We clean the tweets and break them out into tokens and than analysis each word using Bag of Word concept and than rate each word on the basis of the score wheter it is positive, negative and neutral.
We used Naive Baye's Classifier as our base.
The big data phenomenon has confirmed the achievement of data access transformation. Sentiment analysis (SA) is one of the most exploited area and used for profit-making purpose through business intelligence applications. This paper reviews the trends in SA and relates the growth in the area with the big data era.
Sentiment mining- The Design and Implementation of an Internet PublicOpinion...Prateek Singh
Sentiment mining paper presentation, database mining and business intelligence.
The Design and Implementation of an Internet PublicOpinion Monitoring and Analysing System
Project Report for Twitter Sentiment Analysis done using Apache Flume and data is analysed using Hive.
I intend to address the following questions:
How raw tweets can be used to find audience’s perception or sentiment about a person ?
How Hadoop can be used to solve this problem?
How Apache Hive can be used to organize the final data in a tabular format and query it?
How a data visualization tool can be used to display the findings?
Sentiment analysis of Twitter data using pythonHetu Bhavsar
Twitter is a popular social networking website where users posts and interact with messages known as “tweets”. To automate the analysis of such data, the area of Sentiment Analysis has emerged. It aims at identifying opinionative data in the Web and classifying them according to their polarity, i.e., whether they carry a positive or negative connotation. We will attempt to conduct sentiment analysis on “tweets” using various different machine learning algorithms.
This is small twitter sentiment analysis project which will take one keyword(which is the primary way of storing the tweet in Twitter) and number of tweets, and gives you the pictorial representation of the overall sentiment.
Multimedia data minig and analytics sentiment analysis using social multimediaKan-Han (John) Lu
● The growing importance of sentiment analysis coincides with the popularity of social network platform (Facebook, Twitter, Flickr).
● A tremendous amount of data in different forms including text, image, and videos makes sentiment analysis a very challenging task.
● In this chapter, we will discuss some of the latest works on topics of sentiment analysis based on visual content and textual content.
Sentiment Analysis also known as opinion mining and Emotional AI
Refers to the use of natural language processing, text analysis, computational linguistics and biometrics to systematically identify, extract, quantify and study affective states and subjective information.
widely used in
Reviews
Survey responses
Online and social media
Health care
Sentiment mining- The Design and Implementation of an Internet PublicOpinion...Prateek Singh
Sentiment mining paper presentation, database mining and business intelligence.
The Design and Implementation of an Internet PublicOpinion Monitoring and Analysing System
Project Report for Twitter Sentiment Analysis done using Apache Flume and data is analysed using Hive.
I intend to address the following questions:
How raw tweets can be used to find audience’s perception or sentiment about a person ?
How Hadoop can be used to solve this problem?
How Apache Hive can be used to organize the final data in a tabular format and query it?
How a data visualization tool can be used to display the findings?
Sentiment analysis of Twitter data using pythonHetu Bhavsar
Twitter is a popular social networking website where users posts and interact with messages known as “tweets”. To automate the analysis of such data, the area of Sentiment Analysis has emerged. It aims at identifying opinionative data in the Web and classifying them according to their polarity, i.e., whether they carry a positive or negative connotation. We will attempt to conduct sentiment analysis on “tweets” using various different machine learning algorithms.
This is small twitter sentiment analysis project which will take one keyword(which is the primary way of storing the tweet in Twitter) and number of tweets, and gives you the pictorial representation of the overall sentiment.
Multimedia data minig and analytics sentiment analysis using social multimediaKan-Han (John) Lu
● The growing importance of sentiment analysis coincides with the popularity of social network platform (Facebook, Twitter, Flickr).
● A tremendous amount of data in different forms including text, image, and videos makes sentiment analysis a very challenging task.
● In this chapter, we will discuss some of the latest works on topics of sentiment analysis based on visual content and textual content.
Sentiment Analysis also known as opinion mining and Emotional AI
Refers to the use of natural language processing, text analysis, computational linguistics and biometrics to systematically identify, extract, quantify and study affective states and subjective information.
widely used in
Reviews
Survey responses
Online and social media
Health care
RockYou's Raymond Chan gave an informative presentation about OpenSocial at the Girls in Tech Developer Summit November 19, 2008 in San Francisco. Raymond gave a short history of OpenSocial and a lot of detailed information on coding for OpenSocial.
Who are the top influencers and what characterizes them?Nicola Procopio
A method capable of finding influential users by exploiting the contents of the messages posted by them to express opinions on items, by modeling these contents with a three-layer network.
Machine Learning in Static Analysis of Program Source CodeAndrey Karpov
Machine learning has firmly entrenched in a variety of human fields, from speech recognition to medical diagnosing. The popularity of this approach is so great that people try to use it wherever they can. Some attempts to replace classical approaches with neural networks turn up unsuccessful. This time we'll consider machine learning in terms of creating effective static code analyzers for finding bugs and potential vulnerabilities.
50+ thinkers and planners within MSLGROUP share and discuss inspiring projects on corporate citizenship, crowdsourcing and storytelling on the MSLGROUP Insights Network. Every week, we pick up one project and do a deep dive into conversations around it -- on the MSLGROUP Insights Network itself but also on the broader social web -- to distill insights and foresights. We share these insights and foresights with you on our People’s Insights blog and compile the best insights from the network and the blog in the iPad-friendly People’s Lab Quarterly Magazine, as a showcase of our capabilities. This week, our topic is Facebook Timeline Apps. For more, see:http://peopleslab.mslgroup.co
Building a Raspberry Pi Robot with Dot NET 8, Blazor and SignalR - Slides Onl...Peter Gallagher
In this session delivered at Leeds IoT, I talk about how you can control a 3D printed Robot Arm with a Raspberry Pi, .NET 8, Blazor and SignalR.
I also show how you can use a Unity app on an Meta Quest 3 to control the arm VR too.
You can find the GitHub repo and workshop instructions here;
https://bit.ly/dotnetrobotgithub
Google Calendar is a versatile tool that allows users to manage their schedules and events effectively. With Google Calendar, you can create and organize calendars, set reminders for important events, and share your calendars with others. It also provides features like creating events, inviting attendees, and accessing your calendar from mobile devices. Additionally, Google Calendar allows you to embed calendars in websites or platforms like SlideShare, making it easier for others to view and interact with your schedules.
14. The scores and percentages calculated is plotted into graphs.
15. Some of the types are : - Pie charts - Bar chart - Stacked chart
16. How? Example User N o K I a https://graph.facebook.com/search?q=nokia { "data": [ { "id": "100001027577079_189474574430127", "from": { "name": "MubianaChitaani", "id": "100001027577079" }, "message": "Pipo any1 using nokia 6230i!!!!smbdynidshlp,help!!", "type": "status", "application": { "name": "Mobile", "id": "186529194704290" }, "created_time": "2011-04-06T18:47:34+0000", "updated_time": "2011-04-06T18:47:34+0000" } Scoring ALGO
17. Why? Application Commercial To analyze market trends and public choices. To detect public mood towards particular product. To collect user feedback. To predict share market peaks and valleys. Social Surveys, researches for field of psychology. To analyze various societies. To detect psychological disorders. Public To support common men decisions providing him society’s views. To find help in new locations. Helps understanding common things.
23. Will be? Future Scope Will include database for further analytics. It is expected in future to provide results from all the popular social networking sites. To develop for psychological studies. Will provide drill down facilities. To include spelling and linguistic mistakes. Learning process(NLP) for Word list.
24. Conclusion Different from simple search engines. High flexibility. User friendly output(graphical aid). Applications will keep emerging as users will use it. We expect a lot of improvements in our engine, which will keep it maintain market records.