Clustering halal food consumers: A Twitter sentiment analysis

Mostafa, Mohamed M.

doi:10.1177/1470785318771451

Cited by 64 publications

(57 citation statements)

References 99 publications

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“…Companies may consider Twitter and Facebook messages as an electronic form of the traditional word-of-mouth marketing technique (Mostafa, 2018). The present research shows that social media can be used as an extensive focus group useful for marketing and consumer research.…”

Section: Discussionmentioning

confidence: 79%

“…The search included tweets with both keywords coffee and health. To facilitate data elaboration and guarantee adequate coherence to the interpretation, tweets were included only if written in English (Graham et al, 2014;Lamy et al, 2016;Mostafa, 2018;Thelwall et al, 2011). Tweets, retweets and repeated tweets were collected with support of Ncapture 10.…”

Section: 1mentioning

confidence: 99%

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Social media exploration for understanding food product attributes perception: the case of coffee and health with Twitter data

Samoggia

Riedel

Ruggeri

2020

BFJ

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PurposeFood companies and consumers are increasingly interested in healthy food and beverages. Coffee is one of the most commonly consumed beverages worldwide. There is increasing consensus that coffee consumption can have beneficial effects on human body. This paper aims at exploring Twitter messages' content and sentiment towards health attributes of coffee.Design/methodology/approachThe research adopted a utilitarian and hedonic consumer behaviour perspective to analyse online community messages. A sample of 13,000 tweets, from around 4,800 users, that mentions keywords coffee and health was collected on a daily basis for a month in mid-2017. The tweets were categorized with a term frequency analysis, keyword-in-context analysis and sentiment analysis.FindingsResults showed that the majority of tweets are neutral or slightly positive towards coffee’s effects on health. Media and consumers are dynamic Twitter users. Findings support that coffee consumption brings favourable emotions, wellness, energy, positive state of mind and an enjoyable and trendy lifestyle. Many tweets have a positive perception of coffee health benefits, especially relating to mental and physical well-being.Research limitations/implicationsThe high number of users and tweets analysed compensates the limited amount of time of data collection, Twitter messages' restricted number of characters and quantitative software analysis limitations.Practical implicationsThe research provides valuable suggestions for food and beverage industry managers.Originality/valueThis work adds value to the literature by expanding scholars' research on food product attributes perception analysis by using social media as a source of information. Moreover, it provides valuable information on marketable coffee attributes.

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Section: Discussionmentioning

confidence: 79%

Section: 1mentioning

confidence: 99%

Social media exploration for understanding food product attributes perception: the case of coffee and health with Twitter data

Samoggia

Riedel

Ruggeri

2020

BFJ

View full text Add to dashboard Cite

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“…However, in our digitized media environment, Automated Content Analysis (ACA) has gained importance and popularity [43]. Recently, quantitative techniques for extracting intelligence from food-related tweets as sentiment analysis [44,45] using Partition Around Medoids (PAM) and clustering algorithms [46]; or text analysis using Machine Learning (ML) such as Support Vector Machine (SVM) and hierarchical clustering [47], or n-gram [14] are being used.…”

Section: Literature Reviewmentioning

confidence: 99%

Identification and Analysis of Strawberries’ Consumer Opinions on Twitter for Marketing Purposes

Borrero

Zabalo

2021

Agronomy

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Data are currently characterized as the world’s most valuable resource and agriculture is responding to this global trend. The challenge in that particular field of study is to create a Digital Agriculture that help the agri-food sector grow in a fair, competitive environment. As automated machine learning techniques and big data are global research trends in agronomy, this paper aims at comparing different marketing techniques based on Content Analysis to determine the feasibility of using Twitter to design marketing strategies and to determine which techniques are more effective, in particular, for the strawberry industry. A total of 2249 hashtags were subjected to Content Analysis using the Word-count technique, Grounded Theory Method (GTM), and Network Analysis (NA). Findings confirm the results of previous studies regarding Twitter’s potential as a useful source of information due to its lower execution and analysis costs. In general, NA is more effective, cheaper, and faster for Content Analysis than that based both on GTM and automated Word-count. This paper reveals the potential of strawberry-related Twitter data for conducting berry consumer studies, useful in increasing the competitiveness of the berry sector and filling an important gap in the literature by providing guidance on the challenge of data science in agronomy.

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“…For example, Philander and Zhong (2016) analysed tweets to examine customer perceptions about the services provided by resorts, while Yu and Wang (2015) analysed US sports fans' 2014 World Cup tweets. Mostafa (2018Mostafa ( , 2019) examined Tweets on halal food, while Oliveira, Cortez, and Areal (2017) used Twitter data to forecast useful stock market variables, including returns, volatility, and trading volume of a diverse dataset of indices and portfolios. Nguyen et al (2018) focussed on Twitter sentiments towards and in association with low birth weight and pre-term birth in the USA.…”

Section: Twittermentioning

confidence: 99%

Examining what people tweet in relation to halal cosmetics-related topics

Sulaiman

Feizollah

Anuar

et al. 2020

Cogent Arts & Humanities

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Twitter is one of the many communications means connecting groups of users with similar interests. This study analyses tweets related to halal cosmetics in order to gain insights about halal cosmetics chatter on Twitter. The researchers extracted Twitter data related to halal cosmetics (2008 to 2018) using English and Bahasa Malaysia keywords and examined a sample of 19,449 tweets. They found that halal cosmetics began to gain popularity in 2014 and, in terms of geo-location, the highest number of tweets pertaining to halal cosmetics came from Indonesia, followed by Malaysia and the United Kingdom. Nevertheless, they found that only 17 percent of the users revealed their geo-location. This study examines the content of tweets related to halal cosmetics with the aim to help increase knowledge about issues individuals are discussing when social networking with others about halal cosmetics. Specifically, the study analyses the text of the tweets, categorises them as information, promotions or advice, and examines the halal cosmetics brands/ products that are most tweeted. The researchers found that most of the tweets were either providing information or promoting a particular product or event. The study also identified the top twenty-five brands tweeted. The findings could help the halal cosmetics players to strategize their future marketing plans.

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Clustering halal food consumers: A Twitter sentiment analysis

Cited by 64 publications

References 99 publications

Social media exploration for understanding food product attributes perception: the case of coffee and health with Twitter data

Social media exploration for understanding food product attributes perception: the case of coffee and health with Twitter data

Identification and Analysis of Strawberries’ Consumer Opinions on Twitter for Marketing Purposes

Examining what people tweet in relation to halal cosmetics-related topics

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