hack2innovate I think so it is absolutly right. In a world where “one angry tweet can torpedo a brand,”1 corporations need to embrace all possibilities. Social media2 have transformed the business and communication landscape and organizations appear to, reluctantly or willingly, recognize this change. Evolving patterns of communication, collaboration, consumption, and innovation have created new domains of interactivity for companies and stakeholders. In this changed scenario, there are opportunities for experimentation and correction, yet challenges abound. As on date, there are no definitive methodologies nor there is a ‘one-size-fits-all’ formula that can be applied to all situations for optimum results. What is definite, though, is that social media communication is the new mantra for influence and can have a huge impact on corporate reputation (CR), “the single most valued formal asset”3 that “may enable firms to charge premium prices, attract better applicants, enhance their access to capital markets and attract investors.”4 Data from the United Kingdom and the United States over the last four years show a growing trend and shift in consumer preference for the use of digital media. No longer are consumers and customers dependent on traditional and company-controlled channels of mass communication. It is estimated that by 2018 there will be close to 225 million users in India. Over the last two years, urban India registered a growth of 35 per cent and rural India, 100 per cent.5 With 75 per cent of India’s online population as digital consumers,6 small wonder that digital is the new mantra. Even as traditional media remain valid, being relevant demands a strategic shift towards social-mediated dialogue, engagement, and conversation. This traction towards an “architecture of participation”7 has just begun with a promising ecosystem.
The Effects of Twitter Sentiment on Stock Price Returns - PLOS:-
The recent technological revolution with widespread presence of computers and Internet has created an unprecedented situation of data deluge, changing dramatically the way in which we look at social and economic sciences. The constantly increasing use of the Internet as a source of information, such as business or political news, triggered an analogous increasing online activity. The interaction with technological systems is generating massive datasets that document collective behavior in a previously unimaginable fashion [1, 2]. Ultimately, in this vast repository of Internet activity we can find the interests, concerns, and intentions of the global population with respect to various economic, political, and cultural phenomena.
Among the many fields of applications of data collection, analysis and modeling, we present here a case study on financial systems. We believe that social aspects as measured by social networks are particularly useful to understand financial turnovers. Indeed, financial contagion and, ultimately, crises, are often originated by collective phenomena such as herding among investors (or, in extreme cases, panic) which signal the intrinsic complexity of the financial system [3]. Therefore, the possibility to anticipate anomalous collective behavior of investors is of great interest to policy makers [4–6] because it may allow for a more prompt intervention, when appropriate.
State-of-the-art. We briefly review the state-of-the-art research which investigates the correlation between the web data and financial markets. Three major classes of data are considered: web news, search engine queries, and social media. Regarding news, various approaches have been attempted. They study: (i) the connection of exogenous news with price movements [7], (ii) the stock price reaction to news [8, 9]; (iii) the relations between mentions of a company in financial news [10], or the pessimism of the media [11], and trading volume; (iv) the relation between the sentiment of news, earnings and return predictability [12], (v) the role of news in trading actions [13], especially of short sellers [14]; (vi) the role of macroeconomic news in stock returns [15]; and finally (vii) the high-frequency market reactions to news [16].
There are several analyses of search engine queries. A relation between the daily number of queries for a particular stock, and daily trading volume of the same stock has been studied by [17–19]. A similar analysis was done for a sample of Russell 3000 stocks, where an increase in queries predicts higher stock prices in the next two weeks [20]. Search engine query data from Google Trends have been used to evaluate stock riskiness [21]. Some other authors used Google trends to predict market movements [22]. Also, search engine query data have been used as a proxy for analyzing investor attention related to initial public offerings (IPOs)