Investigation in the influences of public opinion indicators on vegetable prices by corpora construction and WeChat article analysis

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

“…Agricultural product price fluctuations are affected by endogenous factors, macroeconomic factors, and external uncertainties. The theory of agricultural economics states that agricultural product price fluctuations are mainly affected by endogenous factors, such as the relationship between supply and demand ( Li et al, 2020c ) and the price of crude oil, as any changes in agricultural production and transportation costs flow on to product prices ( Fowowe, 2016 ; Wei Su et al, 2019 ). Changes in money supply and international agricultural prices caused by macroeconomic monetary policy can also impact domestic agricultural prices ( Durevall et al, 2013 ); for example, Liu et al (2020) found that exchange rate changes triggered agricultural price fluctuations.…”

“…The risk and uncertainties associated with the COVID-19 pandemic caused unnecessary fear and anxiety ( Islam et al, 2020 ), with these negative emotions tending to spread rapidly on the internet and impacting individual behavior and decision-making ( Nicomedes and Avila, 2020 ). This means that the resident content posted on social media can be an important data source for the study of effects of the COVID-19 pandemic and can assist in establishing effective disease control policies ( Li et al, 2020c ). The pandemic news spread rapidly across social media, which resulted in an increase in the public insecurity about possible goods scarcities and panic buying ( Arafat et al, 2020 ; Prentice et al, 2020 ), which in turn led to unfounded rumors and fake news that further aggravated the panic.…”

A Bibliometric Analysis of Literature on Vegetable Prices at Domestic and International Markets—A Knowledge Graph Approach

“…Scholars are based on HP filtering the hybrid neural network structure of the processor [39] predicts the price of vegetables in linear and nonlinear modes, effectively reducing the risk of vegetable farmers; scholars also combine the fruit fly algorithm (FOA) with the induced ordered weighted average (IWOA), improve the prediction accuracy [40], by establishing a seasonal SARIMA model to predict the monthly price of tomato wholesale prices [32]. In addition, some scholars link internet public opinion with vegetable prices, and construct a combined volume through analysis of internet public opinion the mixed prediction model of product neural network and corpus, and eliminate the seasonal effect of price [41], combined with natural language processing (NLP), convolutional neural network (CNN) and classic economic methods, to carry out large-scale public opinion Subject modeling, research shows that online public opinion has an impact on the fluctuation of vegetable prices, which can be used as a potential factor in predicting vegetable prices [42]. In addition, seven indicators are selected using the ICAVP algorithm to establish a better vegetable price early warning system [43].…”

Susceptible user search for defending opinion manipulation

“…As the cyber space becomes an indispensable part of people’s daily life, the online opinions impact the off-line marketing [19] and public security [20] of the society. This induces malicious individuals to develop various attacks for benefits [7] , [21] , meanwhile inspires researchers to engage in the corresponding defense [22] , [23] .…”