Japanese food. A tailor made Sentiment Analysis

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Transcription:

Japanese food A tailor made Sentiment Analysis

Mackerel, dashimaki egg, tofu in kaminabe

Half Linguist Half Data Scientist EDUARDO VALENCIA evalencia@meaningcloud.com @eduardovalencia

Most important lesson learnt after 30 years dedicated to Linguistics and Natural Language Processing 4

1. Languages are tricky! 5

2. Natural Language Processing is definitely hard! 6

3. And sentiment Analysis damn hard! 7

4. Success = Technology + intelligent adaptation When skilled linguists adapt the software to create a domain-specific features, these tools reach their maximum effect!!

Yelp Reviews of Japanese restaurants in London

Restaurant Shoryu Ramen Shoryu Ramen Shoryu Ramen Shoryu Ramen Shoryu Ramen Shoryu Ramen Shoryu Ramen Review For a chain, Shoryu is quite good and I went twice during my week in London because I love ramen that much. The ramen is definitely better than some that Ive had before which is a good thing. I tried multiple types and they all had unique tastes to them that made them worthwhile. Some appetizers were tried as well and they had varying degrees of success. The pork belly buns are good but certainly there are better. The brussel spout tempura...uhhhhh not We ordered a Shoryu Ganso Tonkotsu, their signature dish with extra meat, and also some fried gyoza. We finished our ramen and also our beer, and waited long for the gyoza. So we had to ask, and it seems they had forgotten about this order. They apologized and made the food right away when we pointed that out, so it was not the end of the world. But normally the gyoza should have come before the ramen as gyoza is We ordered the gyoza and pork and prawn buns to share. Then I ordered the curry ramen The sides came first which I was glad about being staring. The gyoza was freshly cooked and mouth-wateringly good. The pieces of meat inside were chunky and they just went Now, to the buns, it was the first time I'd ever had a 'bun' and I absolutely LOVED them. Whatever that weird type foldy bread is, it's amazing and the toppings were superb. I Next, the ramen. Gosh it was good - garlic, curried soupy goodness with bites sized pieces of friend chicken breast, veg, seaweed and egg floating within. Just perfection. The curry had an almost katsu taste to it which I enjoyed and with the extra clove of garlic, I was in a ramen dream. It was slightly salty but I am a fan of salt so no complaints here!

MonkeyLearn MetaMind AlchemyAPI Aylien Idol Datumbox

MeaningCloud Plato is my friend, but truth is a better friend

Food is relatively fine but definitely not worth the hassle you have to put up with to get it. We were surrounded by incredibly rowdy customers who were shouting and screaming in a basement of a dirty and outdated restaurant with terrible decor. The toilet was filthy and there was only one for a man and a woman. So be prepared to queue

Limitations of sentiment analysis For Japanese restaurants we need to know opinions about Dishes: sushi, sashimi, ramen, gyoza, Quality characteristics: price, atmosphere, etc.

Sentiment analysis in MeaningCloud Identify sentiment (positive/negative/neutral or no polarity) Document-level (overall) Sentence-level Associated to mentioned entities/concepts/attributes The ramen is good, but the restaurant is horrible

Food is relatively fine but definitely not worth the hassle you have to put up with to get it. We were surrounded by incredibly rowdy customers who were shouting and screaming in a basement of a dirty and outdated restaurant with terrible decor. The toilet was filthy and there was only one for a man and a woman. So be prepared to queue This document is: positive (+0.299) Extracted themes Sentiment Terrible service -0.75 relatively fine +0.88 rowdy customers +0.50 outdated restaurant +0.31 terrible decor -0.75

Food is relatively fine but definitely not worth the hassle you have to put up with to get it. We were surrounded by incredibly rowdy customers who were shouting and screaming in a basement of a dirty and outdated restaurant with terrible decor. The toilet was filthy and there was only one for a man and a woman. So be prepared to queue man concept 2 Top>Person NONE toilet concept 3 Top>Location>Facility N+ basement concept 4 Top>Location>Facility N restaurant concept 5 Top>Location>Facility N woman concept 6 Top>Person NONE food concept 7 Top>Product>Food P service concept 8 Top>Product>ProfessionalService N+ customer concept 9 Top>Organization N

We ordered the gyoza and pork and prawn buns to share. Then I ordered the curry ramen in the others section extra Top>OtherEntity>Vocation NONE bun Top>Product>Food>CookedPlate P shrimp Top>LivingThing>Animal>Invertebrate P

1. Personal dictionary of entities and concepts

Personal dictionary of entities and concepts Restaurant Dish Evaluation Ramen Sushi Sashimi etc. Price Staff Atmosphere etc.

2. Rule Engine and Sentiment Analysis Beyond rules based on text strings Applies morphosyntactic analysis + ontology Feature highlights Linguistic information of terms: Morphosyntactic: function, lemma/form Semantic: type, theme, geography Expressions: literal, regular, proximity Logical operators: AND, OR, NOT Text Rules Codes

Personal sentiment model Polarity of expressions to share POLARITY = NONE Polarity depending on context portion slice TOGETHER IN THE SAME SENTENCE WITH small tiny meager POLARITY = NEGATIVE Polarity depending on context and function service TOGETHER IN THE SAME SENTENCE WITH slow AND ACTING AS <noun> POLARITY = NEGATIVE

Quality of service

Conclusion The highest-quality sentiment analysis Attribute-level analysis Personal dictionaries, to focus the analysis on aspects of interest Personal sentiment models to adjust polarity depending on the domain

Try me for free at meaningcloud.com is a company MADRID, ES Av. del Llano Castellano, 13 5º A 28034 Madrid MEXICO DF, MX Altavista Business Center Av Universidad 1134 1º Col. Xoco Del. Benito Juárez, 03330 NEW YORK, US 54 W. 40th St. New York, NY 10018