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Why People Hoarded Toilet Paper at the Beginning of the Pandemic ?

A text analytics study of Twitter data using Wordstat 8

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We have all heard the stories well-nigh people virtually the world stocking up on utilitarian goods such as toilet paper, soap, disinfectant, and other products at the whence of the COVID-19 lockdown. News reports showing waterless store shelves brought the situation home and created the visitation of shortages. In fact, we have learned that for many products the shortages were temporary. The uneaten ownership was exacerbated by news items and social media reports. The reality is that people were over purchasing, and by doing so they stretched the retail networks just-in-time supply chain. Factories were standing to produce the same value of toilet paper as unchangingly and once the panic subsided the store shelves returned to normal. But what caused the initial flurry of activity? Why did it abate? What were the factors influencing this behavior?

In their paper Barnes, Diaz, and Arnaboldi (2020) looked to social media for some answers. They studied increasingly than 24,000 Italians’ comments on Twitter to try to understand the motivations and how government announcements impacted them. They placid increasingly than 59,000 tweets over 14 days.

The authors explored compensatory tenancy theory (CCT) which suggests that panic ownership is a subconscious solution to a problem.

In effect, CCT suggests panic ownership helps individuals finger increasingly in tenancy of an uncertain situation, plane if such measures are not required realistically. Under situations of limited control, individuals are worldly-wise to regulate their feelings of tenancy via volitional ways (Thompson, 2009). Thus, choices in consumption policies may form illusory beliefs of an effect on an individual’s environment (Landau, Kay, & Whitson, 2015). Increasingly specifically, CCT builds on existing literature that suggests consumers’ desire to seek structure in their choices and policies (Hamerman & Johar, 2013; p. 3)

The Twitter data for the study was placid from the Twitter API focusing on the hashtag #iorestoacasa which translates as, I stay at home. The authors built dictionaries using WordStat 8 to measure concepts such as utilitarian, purchasing, lack of perceived control, and anxiety. Utilitarian, purchasing, lack of perceived tenancy concepts dictionaries were built from the ground up. For fear and anxiety, the wordlist LIWC2015 (Pennebaker et al., 2015) was used as the base. The wordlist was then tailored to the data set and extended using the WordNet functionality and wordlist builder in WordStat 8.

The table unelevated from the paper shows some examples.

Concept Example Wordlist Items
Anxiety (90 words) afraid, alarm, confused, distraught, frantic, insecure, nervous, panic, scared, tense, terrified, threat, twitchy, uncomfortable, upset, worry.
Lack of Perceived Tenancy (206 words) Defenseless, dependent, helpless, hopeless, impotent, incapable, ineffective, pathetic, powerless, surrender, unable, voiceless, weak.
Utilitarian (281 words) cleaner, domestic, household, functional, packet, practical, pragmatic, prepare, provision, purpose, standard, tinned, useful, utility, vacuum.
Purchasing (80 words) bargain, bought, cart, customer, delivery, discount, mall, outlet, procure, purchased, shopping, store, supermarket, transact, impulse-buy, vendor.

Table 1. Concept Dictionaries and Examples.

The authors measured these concepts on Twitter, in-line with two government announcements made at variegated times during the study period.  The icon unelevated from the paper shows 77% of cases were during the government utterance 1 window and 36% during the government utterance 2 window. The authors note that the second utterance was increasingly detailed than the first which may be one of the reasons for less activity.

Text analytics of Twitter data using WordStat 8.0

Text analytics study of Twitter data using wordstat well-nigh Hoarding Toilet Paper at the whence of the COVID-19 lockdown

The wringer and findings are very interesting and instructive to academics studying CCT and to retailers and governments both in terms of how to prepare for the early stages of a pandemic type of situation and how weightier to communicate information to the population.

 

Barnes, S. J., Diaz, M., & Arnaboldi, M. (2020). Understanding panic ownership during COVID-19: A text analytics approach. Expert Systems with Applications, 114360.