scholarly journals Measuring information flux between social media and stock prices with Transfer Entropy

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257686
Author(s):  
Román Alejandro Mendoza Urdiales ◽  
Andrés García-Medina ◽  
José Antonio Nuñez Mora
Keyword(s):  
Public Opinion ◽  
Stock Prices ◽  
General Public ◽  
Transfer Entropy ◽  
Data Set ◽  
Deep Relationship ◽  
Flow Of Information ◽  
General Opinion ◽  
Clear Information ◽  
Processing Language

Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and company mentioned. We proposed the construction of a Sentiment Index applying a Natural Processing Language algorithm and structuring the sentiment polarity for each data set. Bootstrapped Simulations of Transfer Entropy were performed between stock prices and Sentiment Indexes. The results of the Transfer Entropy simulations show a clear information flux between general public opinion and companies’ stock prices. There is a considerable amount of information flowing from general opinion to stock prices, even between different Sentiment Indexes. Our results suggest a deep relationship between general public opinion and stock prices. This is important for trading strategies and the information release policies for each company.

Dynamic Relationship between Crude Oil and Stock Prices in India: Before And After the Subprime Financial Crisis 2008

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 96-104
Author(s):  
P. Sakthivel ◽  
S. Rajaswaminathan ◽  
R. Renuka ◽  
N. R.Vembu
Keyword(s):  
Financial Crisis ◽  
Crude Oil ◽  
Stock Prices ◽  
Oil Prices ◽  
Energy Index ◽  
Data Set ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Long Run ◽  
Before And After

This paper empirically discovered the inter-linkages between stock and crude oil prices before and after the subprime financial crisis 2008 by using Johansan co-integration and Granger causality techniques to explore both long and short- run relationships.  The whole data set of Nifty index, Nifty energy index, BSE Sensex, BSE energy index and oil prices are divided into two periods; before crisis (from February 15, 2005 to December31, 2007) and after crisis (from January 1, 2008 to December 31, 2018) are collected and analyzed. The results discovered that there is one-way causal relationship from crude oil prices to Nifty index, Nifty energy index, BSE Sensex and BSE energy index but not other way around in both periods. However, a bidirectional causality relationship between BSE Energy index and crude oil prices during post subprime financial crisis 2008. The co-integration results suggested that the absence of long run relationship between crude oil prices and market indices of BSE Sensex, BSE energy index, Nifty index and Nifty energy index before and after subprime financial crisis 2008.

A Comparative Content Analysis of Physician, General Public and Media Opinion Leader Posts Regarding Physician-patient Conflicts on Microblog (Preprint)

2020 ◽  
Author(s):  
Wanqi Gong ◽  
Qin Guo
Keyword(s):  
Content Analysis ◽  
Public Opinion ◽  
General Public ◽  
Public Perception ◽  
Medical Science ◽  
Popular Science ◽  
Opinion Leaders ◽  
Objective Evidence ◽  
Comparative Content ◽  
Physician Patient

BACKGROUND Physician-patient conflicts have increased more than ten times from the 2000s to 2010s in China and arouse heated discussion on microblog. However, little is known about similarities and differences among views of opinion leaders from the general public, physician, and media regarding physician-patient conflict issues on microblog. OBJECTIVE This study aimed to explore how opinion leaders from physician, the general public, and media areas framed the posts on major physician-patient conflict issues on microblog. Findings will provide more objective evidence of trilateral (health profession, general public, and media) attitudes and perspectives on physician-patient conflicts. METHODS A comparative content analysis was conducted to examine the posts (N=545) from microblog opinion leaders regarding the major physician-patient conflicts in China from 2012 to 2017. RESULTS Media used significantly more conflict (M=0.16) and attribution frames (M=0.16) but least popularize medical science frame (M=0.03) than physician (M=0.06, p<0.001; M=0.06, p<0.001; M=0.08, p=0.035, respectively) and general public opinion leaders (M=0.06, p<0.001; M=0.09, p=0.003; M=0.12, p<0.001, respectively). There are no significant differences in the use of conflict, cooperation, negative and popular science frames between general public and physician opinion leaders. CONCLUSIONS This imbalanced use of frames by media would cultivate and reinforce the public perception of physician-patient contradiction. The physician and general public opinion leaders share some commons in post frames, implying that they do not have a fundamental discrepancy on physician-patient conflict issues. It is essential to guide and encourage media microbloggers to make every effort to popularize medical science and improve physician-patient relationships.

Politikberatung der Öffentlichkeit?

2001 ◽  
Vol 2 (1) ◽  
pp. 61-73 ◽  
Author(s):  
Hans Pitlik
Keyword(s):  
Public Opinion ◽  
Collective Action ◽  
General Public ◽  
Policy Advice ◽  
Collective Action Problem ◽  
Academic System ◽  
Countervailing Power

Abstract Due to the incentives of both suppliers and users of policy advice the influence of economists on government decisions is almost negligible. This paper aims to explore the prospects of policy advice addressed to the general public as a countervailing power. It is argued that in order to have some impact on public opinion economists must rely primarily on propaganda and have to overcome a serious collective action problem. Yet, the organization of the academic system provides no incentives for economists to fulfil the role of general-public-oriented advisers.

Inside Trending Topic Algorithm: How Do Human Interactions Drive Public Opinion in an Artificial Environment

2021 ◽  
pp. 089443932110415
Author(s):  
Vanessa Russo ◽  
Emiliano del Gobbo
Keyword(s):  
Public Opinion ◽  
Semantic Network ◽  
Opinion Leader ◽  
Computational Techniques ◽  
Data Sets ◽  
Process Data ◽  
Data Set ◽  
Social Actors ◽  
Human Interactions ◽  
Artificial Environment

The object of this research is to exploit the algorithm of Twitter’s trending topic (TT) and identify the elements capable of guiding public opinion in the Italian panorama. The underlying hypotheses that guide the whole article, confirmed by the research results, concern the existence of (a) a limited number of elements at the base of each popular hashtag with very high viral power and (b) hashtags transversal to the themes detected by the Twitter algorithm that define specific opinion polls. Through computational techniques, it was possible to extract and process data sets from six specific hashtags highlighted by TT. In a first step through social network analysis, we analyzed the hashtag semantic network to identify the hashtags transversal to the six TTs. Subsequently, we selected for each data set the contents with high sharing power and created a “potential opinion leader” index to identify users with influencer characteristics. Finally, a cross section of social actors able to guide public opinion in the Twittersphere emerged from the intersection between potentially influential users and the viral contents.

scholarly journals Demonetisation and Indian Stock Market

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Ruchika Gahlot
Keyword(s):  
Linear Regression ◽  
Real Estate ◽  
Stock Prices ◽  
General Public ◽  
Financial Service ◽  
Medium Term ◽  
Donald Trump ◽  
Cash Transaction ◽  
Indian Stock Market

Demonetisation of 500 and 1000 bank notes was announced by PM Modi on 8th Nov 2016. There were number of speculation relating to its effects on general public and different sectors of Indian economy. This paper studies the effect of demonetisation on stock prices of different sectoral indices and Nifty listed on NSE by using t test, f test and linear regression. The results revealed that Nifty, automobiles, FMCG, Financial service, media and banking and real estate were major sectors affected by demonetisation decision as they are based on cash transaction. The prices of indices of NSE were influenced by S and P 500 in medium term and long term which may be the effect of policy of US president Donald Trump who was elected as President of U.S. on 8th November 2016.

“Dear John”

2021 ◽  
pp. 166-200
Author(s):  
Andrew Rudalevige
Keyword(s):  
Public Opinion ◽  
Executive Branch ◽  
Data Set ◽  
Executive Orders ◽  
Good Management ◽  
Unilateral Action

This chapter presents a new data set of more than two hundred executive orders never signed by the president. However that is interpreted — as good management or as gridlock — something that could have been done “with the stroke of a pen” was not. Here, too, quantitative and archival analysis pair to help us understand why. The results highlight the fact that unilateral action has costs, which at some point outweigh the benefits. Those costs may be rung up in Congress, or the courts, or by public opinion. But as the exploration here shows, they may also be imposed by the executive branch.

Authoritarian Gridlock? Understanding Delay in the Chinese Legislative System

2018 ◽  
Vol 53 (9) ◽  
pp. 1455-1492 ◽  
Author(s):  
Rory Truex
Keyword(s):  
Public Opinion ◽  
Food Safety ◽  
Qualitative Analysis ◽  
Case Studies ◽  
Authoritarian Regimes ◽  
Data Set ◽  
Checks And Balances ◽  
Unique Data ◽  
Chinese Case ◽  
Legislative Processes

Legislative gridlock is often viewed as a uniquely democratic phenomenon. The institutional checks and balances that produce gridlock are absent from authoritarian systems, leading many observers to romanticize “authoritarian efficiency” and policy dynamism. A unique data set from the Chinese case demonstrates that authoritarian regimes can have trouble passing laws and changing policies—48% of laws are not passed within the period specified in legislative plans, and about 12% of laws take more than 10 years to pass. This article develops a theory that relates variation in legislative outcomes to the absence of division within the ruling coalition and citizen attention shocks. Qualitative analysis of China’s Food Safety Law, coupled with shadow case studies of two other laws, illustrates the plausibility of the theoretical mechanisms. Division and public opinion play decisive roles in authoritarian legislative processes.

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