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AbstractThis study uses the interstate political conflict in 2010 to study the impacts of oppositional sentiment on product sales of Japanese‐brand automobiles in China. By using the nationwide automobile registration data in China, we conduct difference‐in‐differences analysis and find direct evidence on Chinese consumers' boycott of Japanese‐brand autos. It is individual buyers rather than business or government entity buyers that boycotted Japanese cars significantly. War memory, nationalist education, and protests contributed to the intensity of boycott activities, and the boycott effect was long‐lasting. Older‐generation buyers boycotted Japanese cars more significantly, but younger‐generation buyers living in cities with historical war experience or patriotic education bases boycotted Japanese cars more actively than their counterparts in other cities.

PurposeThe purpose of this study is to examine the effect of country affinity, ethnocentrism and product quality judgment on self-brand connection regarding both domestic and foreign brands.Design/methodology/approachThe study involved an online experiment and was conducted using online questionnaires. Sampling was done among undergraduate students of a Southwestern university in the US. The data was analyzed using SEM with PLS.FindingsThe results showed, for foreign brands, consumer self-brand connection increased through the effect of country affinity and product quality judgment. For domestic brands, self-brand connection was influenced by ethnocentrism (and not country affinity or product quality judgment).Research limitations/implicationsThis study only focused on one industry (i.e. Television industry), and the authors recommend future studies examine a broader range of industries. Moreover, other country related constructs such as national identity need to be examined in future studies.Practical implicationsMarketers focusing on global branding and international marketing can benefit from the findings of this paper by understanding the routes through which consumers build self-brand connections in foreign vs domestic settings. Additionally, marketers can, more effectively, invest their resources by focusing on the factors that can be influential (i.e. ethnocentrism for domestic brands vs country affinity and product judgment for foreign brands).Originality/valueThis study examines the effect of country affinity, ethnocentrism and product quality judgment for consumers' domestic country as well as a foreign country. Moreover, this study contributes toward the global branding literature by incorporating self-brand connection as a behavioral outcome.

Social media allow consumers to easily share positive or negative information about a brand with other consumers, for instance, through Twitter. Such Twitter use is a source of information that may affect the brand reputation. Therefore, it is important to gain more understanding of how Twitter is employed to evaluate brands and to communicate these evaluations with others. Previous research on Twitter use has shown that tweets about brands are more likely to be positive than negative. The present study integrates an agenda-setting perspective with studies on word of mouth and services marketing, which have suggested that this finding may be different for services than for goods. A quantitative content analysis of 1,920 Dutch tweets for 24 different brands was performed. The analysis showed that services received significantly more negative sentiment tweets than products. Implications of these results for monitoring consumers are discussed.

This study aims to evaluate the empathic brand initiative during the COVID-19 pandemic in Indonesia and analyse the online sentiments toward the philanthropy of corporations, non-profits organisations, citizens and society. Sentiment analysis was conducted on related posts of 15 companies from March to June 2020 with varying preliminary times for each company as the first donor. To complete the perception, the authors conducted a focus group discussion (FGD). Research shows that medium size and small–medium enterprises, such as local cosmetic companies and budget hotel are the first donors, followed by large or multinational companies (MNCs). In contrary with previous research, public perception was not influenced by the amount and the time of giving but was impacted by communication strategies, the empathy of the brand itself, and the company behaviour before COVID-19 period. This research's novelty is the emphatic communication model to create, maintain and protect a company's reputation.

Many emerging social sites, famous forums, review sites, and many bloggers generate huge amount of data in the form of user sentimental reviews, emotions, opinions, arguments, viewpoints etc. about different social events, products, brands, and politics, movies etc. Sentiments expressed by the users has great effect on readers, political images, online vendors. So the data present in scattered and unstructured manner needs to be managed properly and in this context sentiment analysis has got attention at very large level. Sentiment analysis can be defined as organization of the text which is used to understand the mindsets or feelings expressed in the form of different manners such as negative, positive, neutral, not satisfactory etc. This paper explains the implementation and accuracy of sentiment analysis using Tensor flow and python with any kind of text data. It works on embedding, LSTM and Sigmoid layers and finds the accuracy of data in iterative manner for better result

AbstractWhen a brand is disliked, one strategy used to improve consumer sentiment is to make counter‐claims against the reason for dislike. But little is known about the effectiveness of this strategy, or the effect this strategy has on differential judgements towards the brand. Two experimental studies are conducted to shed light on the effectiveness of counterclaim advertising. The results find evidence to suggest that counter‐claim advertising may actually worsen sentiment towards the brand, when the brand is already disliked. The findings suggest that brands do not try to directly counter known reasons for dislike, but instead formulate alternative ways to rebuild trust. Copyright © 2016 John Wiley & Sons, Ltd.

This study applies the collaboration approach of city brand index and city brand personality towards the city branding "Padang Your Motherland". The results of city brand index show that the presence aspect - visitors 'views on international status and reputation globally' gets the highest rating. The aspect of the city brand index of the city of Padang that is relevant to the city branding "Padang Your Motherland" is the presence, place, people, sentiments of feeling, while the indirect is the potential and preconditions. On the other hand, City of Padang city personality scale also shows that some aspects that shape the brand personality of Padang City have direct relevance to the city branding "Padang Your Motherland", namely excitement, skill, and toughness, while the indirect aspects are sincerity and sophistication. This aspect that does not have direct relevance can be a supporter in the personality of Padang City. Based on the results of this study, it is suggested that the Padang City Government pay more attention to the potential aspects and prerequisites in city brand index and aspects of sincerity and sophistication in city brand personality in the development or evaluation of the city branding "Padang Your Motherland".

The South Australian (SA) Moratorium against genetically modified organisms (GMOs): (i) preserves food sovereignty for SA, (ii) it accords with global consumer sentiment, (iii) it validates SA's clean and green and natural image, (iv) it supports premium price agriculture, and (v) it avoids another Holden car crash experience in SA. General Motors recently wielded the axe on the Holden brand in Australia. Sovereignty for Holden had long ago been ceded to Detroit, USA, and, the company in Australia had persisted in ignoring consumer sentiment by promoting sedans (Commodores) long after consumer demand had moved on to SUVs (sports utility vehicles). With a GMO Moratorium, SA maintains sovereignty of its foodscape. Without a GMO Moratorium, the shots are ceded to Dusseldorf (Bayer & Monsanto), Basel and Beijing (Syngenta & ChemChina). Global consumer surveys reveal that consumers do not want GMOs on their plate (e.g. 60% of Chinese consumers say no to GMOs). Germany, Switzerland and China exclude their own GMO companies from selling and growing their own GMO products in their home countries. So, these GMO/pesticide companies seek far away 'mindless jurisdictions' which will allow their products. Australia has 51% of the world's certified organic agriculture hectares, and just 0.4% of the world's GMO hectares. SA is a world leader in Organics and accounts for 40% of the certified organic agriculture hectares of Australia. The SA GMO Moratorium safeguards this important premium sector. GMO crops are 'bargain basement' crops that sell at a price penalty (e.g. 7.2% price penalty for WA GM canola). There is no way of containing or recalling GMOs. Once released into the environment they knit themselves into the genetic fabric of the foodscape, without any mechanism for recall. Most Australian consumers think that GMO foods are unsafe (90% in a recent survey survey), they may be right. There is at present a point of difference that Australia has from USA, also a major food exporter. Food in Australian supermarkets is non-GMO - mandated GMO labelling means that Australian food manufacturers and retailers exclude GMOs. There is no means for effectively segregating GMO crops and nor for avoiding contaminating non-GMO farms. The sensible decision for the Parliament of South Australia is to leave the SA GMO Moratorium in place.

This study investigated social-media-based anti-brand communication. Guided by consumer boycotts and brand cancellation theory, the author conducted a qualitative study based on content analysis of tweets about 59 international brands that remained in Russia after the invasion in February 2022. The research was conducted on Twitter between August 10 and 17, 2022. The study aimed to determine whether brands that have decided to stay in Russia are still exposed to negative WoM, calls for a boycott or brand cancellation after 6 months since the war began. The obtained results made it possible to identify the number of tweets and their content and sentiment. They also showed the dynamics of negative WoM publications on social media and their character. The practical implications are the following: brands exposed to consumer boycotts, depending on their business goals, may decide to adopt a "wait-out" strategy.

International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017 ; The World Wide Web such as social networks, forums, review sites and blogs generate enormous heaps of data in the form of users views, emotions, opinions and arguments about different social events, products, brands, and politics. Sentiments of users that are expressed on the web has great influence on the readers, product vendors and politicians. The unstructured form of data from the social media is needed to be analyzed and well-structured and for this purpose, sentiment analysis has recognized significant attention. Sentiment analysis is referred as text organization that is used to classify the expressed mind-set or feelings in different manners such as negative, positive, favorable, unfavorable, thumbs up, thumbs down, etc. The challenge for sentiment analysis is lack of sufficient labeled data in the field of Natural Language Processing (NLP). And to solve this issue, the sentiment analysis and deep learning techniques have been merged because deep learning models are effective due to their automatic learning capability. This Review Paper highlights latest studies regarding the implementation of deep learning models such as deep neural networks, convolutional neural networks and many more for solving different problems of sentiment analysis such as sentiment classification, cross lingual problems, textual and visual analysis and product review analysis, etc. ; http://thesai.org/Downloads/Volume8No6/Paper_57-Sentiment_Analysis_using_Deep_Learning.pdf