Related papers: Regional inflation analysis using social network d…

This paper evaluates the performance of prominent machine learning (ML) algorithms in predicting Indonesia's inflation using the payment system, capital market, and macroeconomic data. We compare the forecasting performance of each ML…

The presence of multiple fields during inflation might seed a detectable amount of non-Gaussianity in the curvature perturbations, which in turn becomes observable in present data sets like the cosmic microwave background (CMB) or the large…

Centrality is one of the most studied concepts in social network analysis. There is a huge literature regarding centrality measures, as ways to identify the most relevant users in a social network. The challenge is to find measures that can…

User and product information associated with a review is useful for sentiment polarity prediction. Typical approaches incorporating such information focus on modeling users and products as implicitly learned representation vectors. Most do…

We follow up on the study of correlations between GDP's of rich countries. We analyze web-downloaded data on GDP that we use as individual wealth signatures of the country economical state. We calculate the yearly fluctuations of the GDP.…

Macroeconomic variables are known to significantly impact equity markets, but their predictive power for price fluctuations has been underexplored due to challenges such as infrequency and variability in timing of announcements, changing…

Oil price fluctuations severely impact the economies of both oil-exporting and importing countries. High oil prices can benefit oil exporters by increasing foreign currency inflow; however, an economy can suffer from a weakening of the…

This paper aims to show how some popular topics on social networks can be used to predict online newspaper views, related to the topics. Newspapers site and many social networks, become a good source of data to analyse and explain complex…

When an individual purchases a home, they simultaneously purchase its structural features, its accessibility to work, and the neighborhood amenities. Some amenities, such as air quality, are measurable while others, such as the prestige or…

This study proposes content and interaction analysis techniques for a large repository created from social media content. Though we have presented our study for a large platform dedicated to discussions around financial topics, the proposed…

Novel data has been leveraged to estimate socioeconomic status in a timely manner, however, direct comparison on the use of social relations and talent movements remains rare. In this letter, we estimate the regional economic status based…

This study proposes a new method of incorporating emotions from newspaper articles into macroeconomic forecasts, attempting to forecast industrial production and consumer prices leveraging narrative and sentiment from global newspapers. For…

Cryptocurrency is a digital currency that uses blockchain technology with secure encryption. Due to the decentralization of these currencies, traditional monetary systems and the capital market of each they, can influence a society.…

This paper develops a microsimulation model to simulate the distributional impact of price changes using Household Budget Survey data, income survey data and an Input Output Model. The primary purpose is to describe the model components.…

Using images containing information on wealth, this research investigates that pictures are capable of reliably predicting the economic prosperity of households. Without surveys on wealth-related information and human-made standard of…

Social Media has seen a tremendous growth in the last decade and is continuing to grow at a rapid pace. With such adoption, it is increasingly becoming a rich source of data for opinion mining and sentiment analysis. The detection and…

Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather than on patterns of…

Currently, there are more than a dozen Russian-language corpora for sentiment analysis, differing in the source of the texts, domain, size, number and ratio of sentiment classes, and annotation method. This work examines publicly available…

A non-parametric method for ranking stock indices according to their mutual causal influences is presented. Under the assumption that indices reflect the underlying economy of a country, such a ranking indicates which countries exert the…

Modeling user engagement dynamics on social media has compelling applications in user-persona detection and political discourse mining. Most existing approaches depend heavily on knowledge of the underlying user network. However, a large…