:As we know now a day’s Social Networking sites are playing major role in personal as well as business life. As the social networking sites are connecting B2B, B2C and C2C (i.e. Business to Business, Business to Customer and Customer to Customer) they are becoming part of each and every individual life. As per the recent survey done by the Times of India and New York Times almost 60% of the peo...

Motivation and Research Question The plight of the record industry is well known – sales of recorded music have fallen steadily since 2000 as the growth of digital sales has not been fast enough to compensate for the decline of physical cd sales. For example, in 2007 alone physical sales fell 13% to $15.9 billion while digital sales grew by 34% to just $2.9 billion, leading to an overall 8% dec...

Political Hashtag Trends (PHT) is an analysis tool for political leftvs.-right polarization of Twitter hashtags. PHT computes a leaning for trending, political hashtags in a given week, giving insights into the polarizing U.S. American issues on Twitter. The leaning of a hashtag is derived in two steps. First, users retweeting a set of “seed users” with a known political leaning, such as Barack...

We study the magnitude and persistence of the diffusion of exogenous demand shocks on an ecommerce recommendation network. The demand shocks are generated by book reviews on the Oprah Winfrey Show and in the NYTimes, and the recommendation network is generated by Amazon’s copurchase network. We find a strikingly high level of diffusion of exogenous shock through such networks. Neighboring books...

In this work we take advantage of valuable information encoded in taxonomies to improve the quality of recommender systems. We present three strategies that explore the use of taxonomies: (i) category descriptors, (ii) classification features and (iii) category filters. We provide a real-case study over the book domain, in which the recommendation target is a set of 100 news page from The New Y...

We present a demonstration of a newly developed text stream event detection method on over a million articles from the New York Times corpus. The event detection is designed to operate in a predominantly on-line fashion, reporting new events within a specified timeframe. The event detection is achieved by detecting significant changes in the statistical properties of the text where those proper...

This paper presents Linggle Knows, an English grammar and linguistic search engine. Linggle Knows help people writing by displaying lexical and grammatical information extracted from a couple of large scale corpora, including Google Web 1T 5-gram, British National Corpus (BNC), New York Times Annotated Corpus (NYT), etc. It not only describes how a word is genuinely used, but also recommends va...

With the new realities of the digital age, print newspapers are experimenting with different pricing models for their online content. Using NYT’s paywall rollout as a natural experiment, our study finds that a firm’s information pricing policy influences the pattern and effectiveness of online word of mouth (WOM) in social media. Using difference-in-difference-indifferences analysis, we find th...

In this paper we define a simple Relation Extraction system based on SVMs using tree kernels and employing a weakly supervised approach, known as Distant Supervision (DS). Our method uses the simple one-versus-all strategy to handle overlapping relations, i.e., defined on the same pair of entities. The DS data is defined over the New York Times corpus by means of Freebase as an external knowled...

the New York–New Jersey region plunged 51 percent— a drop that far exceeded the 8.4 percent decline in manufacturing jobs nationwide. Some areas within the region were especially hard hit by the employment losses: New York City shed more than two-thirds of its manufacturing jobs, while neighboring northern New Jersey lost 55 percent. Inflation-adjusted, or real, income from manufacturing also f...