Analyzing Twitter for Social TV: Sentiment Extraction for Sports
نویسندگان
چکیده
As TV watchers tweet about how they feel and what they see, they produce valuable information not only about the TV program but also how engaged they are to the program. We have already built a web service, SportSense, which recognizes major events in the US National Football League (NFL) games within 40 seconds after an event takes place by analyzing data retrieved from Twitter in real-time. In this paper, we report our effort to extend SportSense to extract TV watchers‟ sentimental reaction to major events in live broadcast sports games in real-time and present our ongoing work that leverages SportSense for a social TV system that enables TV watchers to better select interesting programs in real-time and to produce personalized program summaries and enables advertisers to customize ads based on recognized events and extracted audience sentiments.
منابع مشابه
2016 Olympic Games on Twitter: Sentiment Analysis of Sports Fans Tweets using Big Data Framework
Big data analytics is one of the most important subjects in computer science. Today, due to the increasing expansion of Web technology, a large amount of data is available to researchers. Extracting information from these data is one of the requirements for many organizations and business centers. In recent years, the massive amount of Twitter's social networking data has become a platform for ...
متن کاملA High-Performance Model based on Ensembles for Twitter Sentiment Classification
Background and Objectives: Twitter Sentiment Classification is one of the most popular fields in information retrieval and text mining. Millions of people of the world intensity use social networks like Twitter. It supports users to publish tweets to tell what they are thinking about topics. There are numerous web sites built on the Internet presenting Twitter. The user can enter a sentiment ta...
متن کاملSentiment Analysis for Social Media
The proposed system is able to collect useful information from the twitter website and efficiently perform sentiment analysis of tweets regarding the Smart phone war. The system uses efficient scoring system for predicting the user’s age. The user ‘gender is predicted using a well trained Naïve Bayes Classifier. Sentiment Classifier Model labels the tweet with a sentiment. This helps in compreh...
متن کاملText Analytics of Customers on Twitter: Brand Sentiments in Customer Support
Brand community interactions and online customer support have become major platforms of brand sentiment strengthening and loyalty creation. Rapid brand responses to each customer request though inbound tweets in twitter and taking proper actions to cover the needs of customers are the key elements of positive brand sentiment creation and product or service initiative management in the realm of ...
متن کاملWhat is the Conversation About?: A Topic-Model-Based Approach for Analyzing Customer Sentiments in Twitter
In Social Commerce customers evolve to be an important information source for companies. Customers use the communication platforms of Web 2.0, for example Twitter, in order to express their sentiments about products or discuss their experiences with them. These sentiments can be very important for the development of products or the enhancement of marketing strategies. The research goal is to an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011