Celiac disease, gluten-allergy or gluten-sensitivity is caused due to glutamine protein from the grains like wheat, rye and barley (collectively called gluten). This protein damages the small intestine and causes stomach pain, bloating, weakness etc. Celiac disease, gluten-allergy or gluten-sensitivity has never really been taken seriously in developing countries like India. However, in developed nations like UK, USA, Canada and other parts of Europe, gluten-free foods have become quite popular. With a prevalence rate of about one in 100 - 133 people worldwide, celiac disease is widespread across the globe and life-long consumption of gluten-free food is recommended treatment for this allergy. Apart from celiac-disease patients, gluten-free foods are also consumed by health conscious people for weight management and high protein diet and by the patients for diabetes, autism and food allergies. Apart from gluten-free flour, biscuits, cookies and snacks, product innovations like gluten-free beers are becoming very popular. Big data including online blogs, articles, and reviews have played a major role in increased sales of gluten-free foods. Thus, analysis of editorial and social media content becomes essential to understand the leading trends in gluten-free foods. This study provided deep insights about positive, negative and neutral sentiments related to gluten-free foods using the data from Perspectory Media Insights and Google Trends. This study also revealed that most of the consumers talked and expected product innovation in food sections like snacks, fast food (pizza, pasta and noodles) and desserts through comments on social and editorial media. Searches were divided into developed (e.g., U.S.A.) and developing nations (e.g., India) to get more details about the consumer preferences. This study would help manufacturers of gluten-free foods to develop food products according to the choices and preferences of consumers. The study is very unique in itself since it combines big data to niche food market of gluten-free foods to draw the valuable consumer preferences using online platforms.
Celiac disease (CD) is an inherited, autoimmune disorder in which proteins from the grains wheat, rye and barley (collectively called gluten) damage the small intestine [
Perceived as a “western disease”, gluten sensitivity has never really been taken seriously in developing countries like India. Due to lack of awareness it has remained highly under-diagnosed [
Online blogs, articles and reviews have played a major role in increased sales of gluten-free foods. Thus, analysis of editorial and social media content becomes essential to understand the leading trends in gluten-free foods. Trend analysis via sentiment analysis and trend impressions provides in-depth analyses of public opinion and causes for those opinion [
Sentiment analysis is a type of natural language processing for tracking the mood of the public about a particular product or topic [
In this study, consumer preferences for gluten-free foods were analyzed on the basis of public sentiment obtained from social and editorial media data. The study provided deep insights about positive, negative and neutral sentiments related to gluten-free foods. The study also revealed that most of the consumers talked and expected product innovation in food sections like snacks, fast food (pizza, pasta and noodles) and desserts on social and editorial media. In this study, especial focus was laid to explore the top searched key words on editorial and social media related to gluten-free foods. Searches were divided into developed (e.g., U.S.A.) and developing nations (e.g., India) to get more details about the consumer preferences. This study would help manufacturers of gluten-free foods to develop food products according to the choices and preferences of consumers. The study is very unique in itself since it combines big data to the niche market of gluten-free foods to draw the valuable consumer preferences using online platforms.
The editorial and social media data was crawled into excel format with help of an American data company “Perspectory Media Insights” [
Other than Perspectory Media Insights, Google Trends [
The editorial and social media data was taken for one year from 2016 to 2017 for this study.
The editorial data and social media data included the following:
- Editorial data―It included online newspapers, articles, research journals, reviews & forums. Data from websites of Celiac Society of India, Celiac Society of America, National Celiac Society of USA, Marketsand Markets report, Mintel and Nielsen database.
- Social media data―It includeddata from Facebook, Twitter, Pininterest, Youtube and Google Plus about gluten-free foods.
- Keywords used to extract the data―Gluten-free*, free from gluten*, wheat-free*, no gluten*, not gluten*, no wheat*, food for celiac*, without gluten*, gluten sensitive* + food, gluten-allergy* + food, celiac* + food, gluten-free + snack*, gluten-free + pizza*, gluten-free + pasta*, gluten-free + chocolate*, gluten-free + drink*, gluten-free + beer*, gluten-free + confectionary*, gluten-free + liquor*, gluten-free + bakery*, gluten-free + fast-food*, gluten-free + cereal*, gluten-free + cornflakes*, gluten-free + wine*, gluten-free + alcohol*, gluten-free + energy drink*, gluten-free + cookies*, gluten-free + savories*, gluten-free + juice*, gluten-free + noodle*.
All these keywords were searched independently for both editorial and social media one by one to prepare the consolidated reported.
Research tool: Perceptual mapping was used as research tool to study the trends of editorial media. Perceptual map was prepared based on weighted score of sentiment, number of articles and percentage share of articles. All the articles of editorial media were read thoroughly and their sentiment was decided based on text mining for each food category. Food categories taken into consideration were flour & mixes, fast food (including pizza & pasta), bakery, cereals & cornflakes, snacks, soft & energy drinks, liquor, confectionary and last category was desserts. Then, positive, negative and neutral sentiments for all articles were compiled into a total number for each food category. Total number of articles
Keywords | Growth Percentage |
---|---|
Gluten free flour | 550% |
Chocolate brownie | 400% |
Tapioca | 300% |
Snack | 290% |
Rolled oats | 250% |
Chocolate chip cookie | 240% |
Peanut butter | 210% |
Amaranth grain | 200% |
Chocolate | 190% |
Muesli | 180% |
Gluten free grains | 170% |
Cookie | 170% |
Multigrain flour | 170% |
Dairy | 160% |
Pasta | 160% |
Organic food | 160% |
Sugar-free | 150% |
Affordable food | 140% |
Biscuits | 140% |
Flaxseed | 130% |
Noodles | 130% |
Namkeen | 130% |
Rice | 120% |
Lactose free food | 120% |
Indian cuisine | 110% |
South Indian dishes | 110% |
Bread | 110% |
Recipe | 100% |
Peanut | 100% |
Butter | 100% |
Brown rice | 100% |
Tasty gluten-free food | 100% |
Egg | 100% |
Cake | 95% |
Millet | 95% |
Oatmeal | 90% |
Cereal | 90% |
Weight loss | 90% |
Desserts | 90% |
Finger millet | 85% |
Almond flour | 85% |
---|---|
Sorghum | 80% |
Veganism | 70% |
Dark chocolate | 60% |
Quinoa | 60% |
Banana | 50% |
Pastry | 50% |
Guargum | 45% |
Pizza | 40% |
Casein | 35% |
Source: Google trends, 2018.
for each category of sentiment were multiplied with their score allotted. Positive sentiment as given a score of 1.5, neutral sentiment was given a score of 1 and negative sentiment was given a score of 0.5. Dimensions used to prepare perceptual map was number of articles for each category and weighted score of each category based on sentiment analysis [
Score calculation for each food category = ( No .of + ve article ∗ 1.5 ) + ( No .of neutral article ∗ 1 ) + ( No .of − ve article ∗ 0.5 ) (1)
% Share for each food category = Total Number of articles for a particular food category Total Number of articles for all the food categories × 100 (2)
1) Sentiment analysis via editorial media
Big data has been coined as a term denoting large or complex data sets. Big data analytics has been considered as the process of examining large data sets to unveil hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The goal of big data analytics is to make business decisions more accurate and prompt by enabling data scientists, predictive modelers and other analytics professionals to analyze large volumes of transaction data and to draw out meaningful results [
Sentiment analysis included the techniques to understand the attitude and mood of a speaker or a writer with respect to some topic or the overall contextual polarity of a document by determining the polarity of a given text as positive, negative, or neutral or as “angry”, “sad”, and “happy” [
Keywords | Growth Percentage |
---|---|
Christmas cookie | 2100% |
Chips & Krispies | 1000% |
Girl scout cookies | 950% |
Organic food | 950% |
Chicken wings | 400% |
Lentils | 300% |
Sugar cookie | 300% |
Taco bell | 250% |
Gluten-free beer | 240% |
Oatmeal | 230% |
Sourdough bread | 200% |
Corn tortilla | 200% |
Cheerios | 200% |
Hot chocolate | 170% |
Carbohydrate | 160% |
Ginger bread | 160% |
Meatballs | 160% |
Dominos | 140% |
Quinoa | 140% |
Whole grain | 140% |
Pasta | 140% |
Pancakes | 130% |
Wrap | 120% |
Cornmeal | 120% |
Cupcakes | 120% |
Pizza crust | 120% |
Donuts | 120% |
Cookies | 120% |
Banana bread | 115% |
Cinnamon roll | 110% |
Snacks | 110% |
Fried chicken | 100% |
Blueberry muffins | 100% |
Doritos | 100% |
Cider | 100% |
Low-carbohydrate diet | 90% |
King Arthur flour | 90% |
Cobbler | 80% |
Nutrition facts label | 80% |
Chickpea | 80% |
Granola | 80% |
Pie | 80% |
---|---|
Bread roll | 80% |
coconut | 80% |
Macaroni and cheese | 70% |
bread | 70% |
Yogurt | 70% |
Cookie | 70% |
Cornbread | 70% |
Waffles | 60% |
Source: Google trends, 2018
Positive (53%)―Leading trends talked about these topics in relation to gluten free foods―organic food, marshmallows, reduce weight, oatmeal, Cheerios, Arrowroot, Peanut butter cookie, King Arthur floor, Panera bread, cider, doughnut, almond meal, quinoa, Dunkin Donuts, high energy level, improves skin and overall health, getting slim, Amaranth.
Neutral (43%)―Leading trends were cookies, allergy, beer, bakery, bread, bun, recipes, cracker, ginger bread, pop-corn, Zucchini fritters, Oatmeal, pan cake, banana bread, pizza.
Negative (4%)―Leading trends were Fad, diabetes, lack of dietary fiber, essential nutrients, French fries, candies, high carbohydrates, irritable bowel syndrome, reduce Bifidobacterium and Lactobacillus, food labels, high cost [
2) Sentiment analysis via social media
Positive (32%)―Rice Krispies, gluten-free bakeries, dark chocolates, gluten-free oats, gluten-free travel and restaurants, gluten-free menu, fish & chips, choco chip cookies, gluten-free flour mixes, nut milk, coconut milk and gluten-free beer, McDonalds gluten-free menu.
Neutral (51%)―Dairy-Free & Vegan Options, Protein Bar, noodle soup, Tortilla Chips, beef and chips, pop-corn, Indian grains, ragi, millets, white rice, jowar, soy and rice flour, gluten-free cornflakes, pizza crust, bread, desserts, baking crust, cake, pan cake cookie.
Negative (17%)―Obesity, high sugar, high carbohydrate, taste, availability on nearby store, wheat contamination, lack of proteins and micro-nutrients, dough binding ability, expensive, skin rash, lactose intolerance and diabetes [
Twitter (49.10% responses) was favorite platform been used the public to put their opinions about gluten-free foods. Many micro blogs were also written by dieticians, nutritionists and food experts, where news recipes of gluten-free foods were discussed along with healthy gluten-free options.
Facebook (23.16% responses) was also popular platform. Many groups and health websites had been formed on Facebook by users of gluten-free foods e.g. Gluten Free, Free From Gluten, Gluten Dude, NYC Celiac Disease and Gluten-Free Meetup, Gluten-free Mama, Celiac group of Mumbai India, Gluten Free, Free From Gluten, Gluten Dude, NYC Celiac Disease and Gluten-Free Meetup, Gluten-free Mama, Celiac group of Mumbai India etc.
Instagram (14.52% responses) has gained high popularity in last few years. Few famous Instagram pages were #glutenfree, gluten.free.me, udisglutenfree, gluten_freeeats, Australian Gluten-Free Life. People posted pictures and share recipes of gluten-free foods.
Blogs (12.22% responses) contributed a lot to create awareness about gluten-free foods. Many blog writers discussed benefits and harms of consuming gluten-free diet. Emphasis was also given to new recipes which were good in taste and high in nutrition.
Youtube (1% response) had lowest response rate. However, few famous Youtube videos on gluten-free foods were What Gluten-Free Really Means, 30 Days Of A Gluten-Free Diet, How to Go Gluten-Free, Gluten Free Foods List, Gluten-Free vs. Gluten Taste Test and Top 10 Gluten Free Dishes [
Few leading brands in India offering gluten-free food were Dr.Schar, Dr. Gluten, Zero G, Kalpana foods, Savorlife, Bewell, Wheafree etc.
Few leading brands in USA offering gluten-free foods were Dr.Schar, Udi’s, Pamela’s, Glutino, Marry gone, Wholefoods, Trader Joe’s, Amy’s, Blue Diamond, Cheerios etc.
Bob red mill, Nature pro, Dr.Gluten, Dr. Schar and Glutino were few famous brands. Soft drinks and energy drinks (6% share of articles) were most of the time naturally gluten-free. Fresh juices or juices with fruit pulp were preferred by users. Cereals and flakes (5% share of articles) had very narrow product brand. Post coco pebbles, gluten-free flakes by Kellogg’s and Nestle, Cheerios Oatmeal were few popular brands [
Big data analysis revealed that maximum online searched about gluten-free foods on editorial and social media were made in developed nations like USA, which had high availability and huge variety of gluten-free foods. Gluten-free
Food Items | Score | No. of Articles | % Share of Articles |
---|---|---|---|
Flour & Mixes | 31626 | 27328 | 10% |
Pizza, pasta, fast food | 47043 | 38054 | 13% |
Bakery | 40718 | 34585 | 12% |
Cereals & Cornflakes | 15454 | 13299 | 5% |
Snacks | 60031 | 49336 | 17% |
Soft & energy drinks | 19375 | 16324 | 6% |
Liquor | 41558 | 33864 | 12% |
Confectionary | 46714 | 37744 | 13% |
Desserts | 44085 | 35891 | 13% |
Source: Author’s own compilation from editorial media data obtained from Perspectory Media Insights data crawlers.
foods in developing nations like India were at a very niche stage, and users here searched for very basic food options like gluten-free flour, biscuits, snacks and noodles. It was observed that data volume of social media was very high compared to editorial media as people posted many things of social media especially on Twitter about gluten-free diet. However, in editorial media only journalists, blog writers and researches publish their findings and opinions about gluten-free food. The study also revealed that most of the consumers talked and expected product innovation in food sections like snacks, fast food (pizza, pasta and noodles) and desserts on social and editorial media. This study would provide direction to manufacturers of gluten-free foods to develop food products according to the choices and preferences of consumers based on ideas and reviews obtained from social and editorial media. The study is very unique in itself since it combines big data to the niche market of gluten-free foods to draw the valuable consumer preferences using online platforms.
I would like to thank Professors at SKRAU, Bikaner India, namely, Dr. Amita Sharma, Dr. Madhu Sharma, Dr. Rajesh Sharma, Dr. MadhuGoel and Dr. AditiMathur for guiding me in this research. Special thanks to Dr. Jonathan Deutsch (Prof. Culinary Arts and Food Science, Drexel University, USA) and Mr. Ashish Sharma (Innovator and leader of Big data practices, USA), for their constant guidance and support throughout the research. My deep thanks to Mr. AdarshTiwari (who was in team of Perspectory Media Insights) for his support in the data extraction process of the research.
The world of social media and editorial is very big and immense. Perspectory Media Insights collects data from 240 million media outlets and Google Trends uses all the web and media portals connected to Google. However still there are chances that a lot of media portals remain touched in this research due to difficultly in accessing them. Thus, the data about editorial and social media on gluten-free foods is mere representation of big data obtained from Perspectory Media Insights and does not claim the data from whole web universe.
The authors claim no conflict of interest with anyone about this research.
Masih, J., Verbeke, W., Deutsch, J., Sharma, A., Sharma, A., Rajkumar, R. and Matharu, P.S. (2019) Big Data Study for Gluten-Free Foods in India and USA Using Online Reviews and Social Media. Agricultural Sciences, 10, 302-320. https://doi.org/10.4236/as.2019.103026
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