Can the word review be used for recommendations

Update: The switch from reviews to Recommendations is now complete. Check out our guide on how to get more Recommendations on Facebook.

Facebook Reviews has become one of the most popular review platforms on the web. They compete with Google Reviews and are overtaking traditional review platforms like Yelp. In an effort to get back to their community-driven roots, Facebook has replaced Facebook Reviews with a new format called Facebook Recommendations.

The most notable change is the removal of ratings. Customers can either recommend or not recommend businesses with testimonials of their experiences using a “Yes” or “No” option. While TrustPilot is adding half-stars to effectively change to a 10-star rating system, Facebook is going from 5 stars to two options: yes or no.

In this post, we’re going to take a deep dive into Facebook Recommendations and explore how they’re replacing Reviews. We’re also going to cover what this means for businesses going forward.

Facebook Recommendations are the new Facebook Reviews, as previously stated. The way they work is simple: when a user views your page, they’ll see a section called Recommendations and Reviews near the top. They also have their own user tab previously labelled “Reviews.”

Whichever way they choose to view your business’ recommendations, users are asked a simple question: ”Do you recommend this business?” They can answer “yes” or “no.” That’s the recommendation part. They can then leave a written review as well.

The Anatomy of a Facebook Recommendation

When a user creates a new recommendation, they can add text, images and tags. The text portion must meet a minimum character requirement. They’re also provided auto-generated tags they can use to round out recommendations.

Before posting recommendations, they can choose to make it viewable to the public, to friends only, to themselves only or to select groups through a custom configuration.

Facebook is hoping this design will spawn rich testimonials that benefit customers and local businesses alike. It starts with the minimum character requirement. By forcing customers to write more than a simple one to two-word review, recommendations can help eliminate short testimonials that do nothing to inform other customers or business owners about the pros and cons of a particular business or location.

Similarly, tags provide a quick summary of a business’ top traits. A few examples include “good for groups,” “cozy atmosphere,” and “child-friendly.”

The same goes for “don’t recommend” responses, only the tags list features negative traits, such as “not child-friendly,” “small portions,” and “slow service.”

How Facebook Recommendations are Replacing Facebook Reviews

Recommendations are replacing Reviews. Instead of a star rating and a bit of text, recommendations are intended to provide more help with better written content, plus images, and descriptive tags.

The way in which recommendations are posted are also quite different from reviews. Instead of appearing publicly on a business’ page and only that business’ page, recommendations can be posted anywhere. Users can even choose to only have them viewed by friends.

Speaking of which, recommendations are also part of Facebook’s quest to get back to its roots as a community-driven platform. Not only can users share recommendations with friends, they can request them by asking friends for recommendations in specific cities.

When their friends reply with recommendations, Facebook will automatically link businesses they recommend to their comments. They’ll even attach reviews and addresses.

Businesses also have more power when it comes to reporting fake or unfair recommendations. You can do this with the “Give Feedback On This Recommendation” setting. When you click this, you can report recommendations as being “not relevant,” “unfair,” “harassment,” and more.

Here are a few additional changes, some of which have already been mentioned:

• The change has been rolled out to local businesses.
• The change is part of Facebook’s overhaul of the UI for mobile business pages.
• The Reviews tab on your page is now the Recommendations tab.
• Along with the Recommendations tab, reviews and recommendations have a higher position on your page.
• Your old reviews and ratings will still be visible.

What This Change Means for Your Business

One of the biggest issues you’re likely worrying about is what’s going to happen with the reviews and ratings you already have. You’ll keep the average rating you already have, and your reviews will still be visible wherever reviews and recommendations are showcased.

If you currently have a low rating and are worried this change may lock you into that score forever, don’t fret. Your rating will still go up and down depending on the number of recommendations and anti-recommendations your business receives. Users simply won’t be able to raise or decrease this overall rating with a star rating. Facebook also hasn’t explained exactly how your new rating is calculated.

How to Get Started with Facebook Recommendations

The transition from Reviews to Recommendations should be seamless as Facebook rolls this feature out to more and more users and businesses. You should ensure Recommendations is enabled regardless. Go to Settings → Templates and Tabs → Reviews (may be labelled Recommendations), and ensure the setting is switched to ON.

You’ll also notice a setting called Share Reviews/Recommendations Tab while you’re there. This is a URL you can use to encourage customers to leave recommendations, though we recommend using the ideal link we talked about in a previous article.

This is something you should do as often as possible when you first transition to Recommendations. This is because tags are only auto-generated for businesses who have received a certain number of recommendations.

The Pros of Facebook Recommendations

The biggest advantage Recommendations has over Reviews is how accessible they are. They’ll appear in areas where customers are most likely to find your business on Facebook, such as Maps. They’ll also appear when customers search for your business or talk about it.

Plus, since Recommendations are designed to enhance Facebook’s community features, recommendations from your potential customers’ closest friends will appear first. This makes the social proof that much more effective and personal for your potential customers.

It’s also easier to report recommendations you feel are fraudulent or harassment. This can be useful if you become the victim of targeted harassment or receive a negative recommendation from a “customer” you’ve never even worked with. Facebook will need to review the claim, but it allows you to get your foot in the door on these issues at the very least.

We should also mention the new forms of content customers can add with Recommendations. Images can provide a preview potential customers can use to get a peek into what your business your business is like, without actually visiting it. They help solidify positive testimonials.

Tags are useful for two reasons. The first is the way they provide a quick summary of your business. Potential customers no longer need to read entire testimonials or dig through your Facebook page to learn whether or not you’re child friendly or serve classic cocktails.

Furthermore, tags can help customers write recommendations in an efficient manner. This is especially true for customers who hesitate to leave reviews when they aren’t sure how to put their experience into words.

The Cons of Facebook Recommendations

Most of the reception around Facebook Recommendations has been positive. However, some businesses and marketers have cited a couple of concerns. First, they’re worried that the high level of accessibility Recommendations provides may lead to a larger number of fraudulent testimonials despite how easy Facebook makes reporting them.

Second, some marketers are worried certain customers may forego leaving recommendations altogether. They’re specifically talking about customers who leave 2-4 star reviews. Because the “yes/no” aspect of Recommendations forces you to choose between two binary options, some marketers are worried this particular group of consumers may feel limited when it comes to writing reviews.

Why are Things Changing?

Facebook was founded by Mark Zuckerberg in 2004 and grew to become the most widely used social network by the time the 2000’s came to a close. This was around the time the platform started adding more features for businesses.

Six or seven years later, the platform now has several controversies and lawsuits under its belt, most of which relate to Facebook’s tendency to favor businesses and investors over the security and privacy of their users.

The biggest example is the data breach that allowed political data firm Cambridge Analytica to access over 50 million Facebook accounts on behalf of President Donald Trump’s 2016 election campaign.

The most recent controversy occurred in late 2018 when Facebook was found guilty of sharing private user data with major tech companies.

Zuckerberg’s Promise to Rebuild Facebook

Mark Zuckerberg published a Facebook post on January 11, 2018. In the post, he vowed to make Facebook more like the platform it used to be. That is, a social network that people use to connect with friends and family.

Here’s a specific excerpt from this post that explains the changes you’re seeing and will see in regards to Facebook’s business features.

We’re making a major change to how we build Facebook. I’m changing the goal I give our product teams from focusing on helping you find relevant content to helping you have more meaningful social interactions.

We started making changes in this direction last year, but it will take months for this new focus to make its way through all our products. The first changes you’ll see will be in News Feed, where you can expect to see more from your friends, family and groups.

As we roll this out, you’ll see less public content like posts from businesses, brands, and media. And the public content you see more will be held to the same standard — it should encourage meaningful interactions between people.”

Businesses and publishers started seeing changes in 2018, and there will likely be more to come as Facebook tests and implements new strategies that favor social interactions over content from businesses.

Facebook Recommendations are simply part of those changes.

A Word from Our Founder

I think the change from Reviews to Recommendations is great in principle. The things they’re trying to accomplish in making reviews more effective and useful are admirable. I still don’t trust Facebook and only recommend using it as a supplement to a great website where you own your own content. 

I also don’t like the fact that they’re taking a 5-star system down to just a binary positive or negative choice. I think there’s often more nuance to a rating. But I get it: either you would recommend it or you wouldn’t.

You might be thinking “but doesn’t Starfish Reviews use that same positive/negative binary system?” Yes, it does. However, we’re not running a review platform taking the final review. Our WordPress plugin is just trying to gauge the user’s feelings toward a business, product, or service, before they go to the actual review platform to leave a review. So we’re trying to make it super simple while leaving the graduated-rating to the review platform. Put simply: I think it’s really effective how we use it, but it’s definitely debatable how Facebook is using it.

The great thing is that Starfish Reviews still works awesome with Facebook Recommendations, and you don’t have to change anything from how you were using it with Facebook Reviews before.

Tevya Washburn (creator of Starfish Reviews)

A Review is a report highlighting someone’s opinion about something, its ideas, the theme, and how it affects someone or something.

Key Takeaways

1. A review evaluates or critiques a work or product, providing opinions and insights on its quality, effectiveness, or value. At the same time, a summary is a condensed version of a work presenting its main points or ideas without offering personal opinions or judgments.
2. Reviews often include personal assessments, recommendations, and comparisons to similar works or products. In contrast, summaries focus on accurately conveying the core content or message of the original work without inserting personal opinions.
3. Both reviews and summaries can be useful for understanding the content or value of a work. Still, they serve different purposes: reviews inform potential consumers or readers about the quality of work, while summaries provide a quick and concise understanding of the original content.

The difference between Review and a Summary is that Review reflects what the partaker thinks about the narrative in all aspects. In contrast, a Summary is just a shortened or condensed version of an artefact that gives the gist of the whole body.

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Review can also mean a revision or subsequent reading of a text or narrative. Whereas, Summary is a broad term which refers to the short restatement reflecting the critical points of any piece of literature, argument or lecture.

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Comparison Table

Parameter of Comparison	Review	Summary
Basic idea	A report on the general idea of the narrative, along with the opinion and analysis of the reviewer.	A concise report of the narrative highlighting its main points.
Persistence	It does not necessarily include the exact points of the subject and extends to external aspects of the issue (like its effect on people).	Holds on to the exact points of the subject, and no extra matter is to be added.
Opinion of the partaker	The reviewer’s opinion plays an essential part and can vary from reviewer to reviewer.	Opinions of the summarizer are not to be included in the summary. It doesn’t matter how the summarizer perceives the subject.
Proceeding	No exact order needs to be maintained for presenting a review.	A summary proceeds in the same order as that of the subject itself.
Size	Includes assessment and critical analysis of the narrative in several aspects and can be lengthy.	It can be pretty short, as it is just a gist of the narrative.

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What is Review?

A review generally delineates the partaker’s opinion about the presented subject. It doesn’t require the exact points of the narrative but revolves around the ideas of it and the way it was presented.

This is used in formal and informal contexts like “a movie review” or “review of a research paper” and can be applied to any subject that can be presented to an audience.

There will exist no final review as every individual contemplates the subject differently. However, the study can be generalized as good or bad.

These reviews don’t necessarily account for the reviewer’s opinions and are closely related to a summary. However, unlike resumes, these reviews don’t have to highlight all the subject’s main points in the same order.

This review is not presented to an audience but is for the use of the partaker himself. The need for this kind of review generally arises when the partaker needs to demonstrate their knowledge on the subject, like examinations.

What is Summary?

A Summary is the concise report of any presented rendering or narrative used for a better and easier understanding. It covers all the text’s main points and gives the story’s essence in the exact order as the report does.

A summary sticks to the points of the subject and doesn’t deviate from them at all. It does not include the summarizer’s opinions or acknowledge any assessment of the issue.

Absoluteness is the backbone of a summary. Since the resume needs to hold on to the exact points of the subject, the summaries from different summarizers must be clear.

Summaries always proceed in the exact nature of the subject, starting from the introduction and terminating where the issue ends.

It is mainly used in academic contexts and for other narratives.

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Main Differences Between Review and Summary

1. A review revolves around the general idea of the subject, whereas a summary holds onto the exact points of the subject.
2. The opinion of the partaker is an integral part of a review, whereas it doesn’t hold any significance in the case of a review.

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References

1. https://en.wikipedia.org/wiki/Review
2. https://dictionary.cambridge.org/dictionary/english/summarize

Emma Smith holds an MA degree in English from Irvine Valley College. She has been a Journalist since 2002, writing articles on the English language, Sports, and Law. Read more about me on her bio page.

In the blog, we will discuss the concept of recommendation system, working approach of review based recommendation system, and python code for implementing it.

What is a Recommendation System?

A recommendation system is a machine learning model that recommends online movies, clothes, blogs, and more to ease your selection process in a way that recommended products are based on your previous history of selection. For example, you’d see “top picks for you” on Netflix after watching a few movies or series on this content platform or you while searching for a few products or clothes on an online shopping platform like Amazon.

You would have gone through the recommendations it is offering to the users, you must’ve also seen the automated playlist created by an audio streaming platform like Spotify for you, all of this is a result of the Recommendation System. (Must read: How Spotify uses Machine Learning models?)

According to the report of Mckinsey, 75% of Netflix views are boosted with the help of recommendations systems whereas around 35% of Amazon purchases are boosted with the help of this machine learning algorithm.

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Stats Showing Growth of Netflix and Amazon with the help of Recommendation System

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Working Approach of Review-Based Recommendation System

While there are many types of recommendation systems such as Popularity based recommendation system, classification model, content-based recommendation system, and more, what we will be discussing is a review-based recommendation system in machine learning and how to implement it using python code. 

Earlier, the recommendations were based on the product trends which means the product that is being used more was recommended almost to everyone, some other approaches used rating histories in order to provide recommendations. Later on, researchers dwelled a little and found that the user’s textual reviews could act as an important data source as input to the recommendation system. So in the review-based recommendation system, both textual reviews, as well as ratings or trends, can be used as input.

The main purpose, for which the review based recommendation system was developed, was to extract relevant information from the user’s textual review of a product, movie, or song. This is how we can amalgamate machine learning with natural language processing. (Related blog: Top 10 Natural Processing Languages (NLP) Libraries with Python)

The Reviews are taken as a dataset and various analysis methods such as text analysis and opinion mining are performed as the first step, later on, a user profile is created on the basis of the result we got through text analysis and opinion mining. The obtained result is engaged with the recommender approaches to achieve precise recommendations for the individual user. (Read also: 6 Dynamic Challenges in Recommendation System).

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Working of Review-Based Recommendation System, Source: ResearchGate

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The textual reviews can be taken as the input with the help of word embeddings instead of TF-IDF approach. We shall see how this model performs on the real-world dataset, our implementation will be based on the customer reviews of Amazon products. 

Python Implementation of Review-based Recommendation system

We are using consumer reviews of amazon products as a dataset, You can download it from Kaggle. 

Step 1: Importing Libraries and reading dataset with the help of pandas Libraries

%matplotlib inline

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

from sklearn.neighbors import NearestNeighbors

from scipy.spatial.distance import cosine

from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer


import re

import string

from wordcloud import WordCloud, STOPWORDS

from sklearn.metrics import mean_squared_error


import csv

df = pd.read_csv(r'Datafiniti_Amazon_Consumer_Reviews_of_Amazon_Products.csv')

Step 2:  Viewing Index

print(df.columns)

print(df.shape)

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Step 3:  Viewing dataset

df.head()

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Now count ‘asins’ ( all non-null values) and also grouping the mean of ‘asins’


count = df.groupby("asins", as_index=False).count()

mean = df.groupby("asins", as_index=False).mean()



dfMerged = pd.merge(df, count, how='right', on=['asins'])

dfMerged

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Step 3:  Taking non-null values of reviews.text, reviews. ratings, and asins.

df1 = df[['reviews.text','reviews.rating','asins']]

df1 = df1.dropna()

df1

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dfProductReview = df.groupby("asins", as_index=False).mean()

dfProductReview.head(3)

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Step 4:  Grouping Reviews of Individual Products

ProductReviewSummary = df1.groupby("asins")["reviews.text"].apply(str)

p = ProductReviewSummary.to_frame()

p['reviews.text'] = p['reviews.text'].str.replace('d+'," ")

p['reviews.text'] = p['reviews.text'].str.replace('n'," ")

p['reviews.text'] = p['reviews.text'].str.strip(" ")


p.shape[0]

-> 24

Step 5:  Tfidf Matrix and Cosine Similarity

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.metrics.pairwise import cosine_similarity

tf = TfidfVectorizer(analyzer='word', ngram_range=(1, 3), min_df=0, stop_words='english')


tfidf_matrix = tf.fit_transform(p['reviews.text'])

print((tfidf_matrix.shape))

-> (24, 9968)


cosine_similarities = cosine_similarity(tfidf_matrix,Y=None,dense_output=False)

cnum = (cosine_similarities.toarray())

print(((cosine_similarities[0][:1,:-19])))

type(cosine_similarities)

Step 6:  Recommendations

def get_recommendations(id):

    print("the product selected is {}".format(p.index[id]))


    a = cosine_similarities.getcol(id)

    val = list(enumerate(a.data))

    #print(val)

    b= dict(val)

    print(b)

    c = sorted(b.items(),key=lambda x:x[1],reverse=True)[1:4]

    k = 1

    for idx in c:

        print("The {} Recommendation is {}".format(k,p.index[idx[0]]))

        k += 1



get_recommendations(0)

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We could have also used the Count vector with KNN machine learning algorithm to get recommendations.

Conclusion

The recommendation system is another wonder of machine learning to ease the selection process, with time, we are seeing methods of implementations are changing, or sometimes new data is becoming a key resource for the machine learning or natural language processing models. (Check also: Machine Learning vs Deep Learning). While everything in the computer science field is moving so fast, we are committed to providing information services as fast as we can at analytics steps.

В этой статье я расскажу, как писать рецензию на книгу на английском языке (how to write a book review), а именно каков план написания рецензии и какие полезные фразы и выражения рекомендуется использовать в ней. Данный вид письменной работы относится к повышенному уровню сложности в отличие от отзыва о прочитанном произведении — An opinion about a book in English.

В качестве примера рецензии предлагается рецензия на английскую книгу писательницы Донны Тартт «Тайная история» (Secret History by Donna Tartt). Если вы еще не читали эту книгу, то ее можно приобрести в интернет-магазине.

Содержание:

1. План написания рецензии
2. Фразы и выражения для рецензии
3. Образец рецензии на книгу на английском языке

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How to Write a Book Review (in details)

1. План написания рецензии на произведение (The Plan of a Book Review)

A book rewiew is written according to the following plan:

1. Introduction (an author, a title, a setting, a plot in short) — Введение (автор, название, местодействия, краткий сюжет)
2. The main part (the plot in details, main characters) — Основная часть (сюжет частично, главные герои)
3. Conclusion  (opinion about the book, reservations, recomendations) — Заключение (личное мнение, недостатки, рекомендации)

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2. Фразы и выражения для рецензии на английском языке (Useful Words for a Book Review)

Общая оценка произведения:

1. a splendid book — великолепная книга
2. a powerful novel — производящий сильное впечатление роман
3. a gripping narrative — захватывающее повествование

О сюжете:

1. be meticulously (intricately) constructed — тщательно продуман
2. be richly detailed (is rich and detailed in plot) — сюжет богат деталями
3. be set in — происходит в
4. be told by — (повествование) ведется от …
5. hold the attention right up to the final page — удерживать внимание читателя до последней страницы
6. The contrast between ….be done most skillfully — Контраст между … выполнен мастерски.

Мнение о произведении:

1. The only reservation of the book… — Единственный недостаток книги…
2. It is difficult to put the book down… — Трудно отложить книгу …
3. I highly recommend the book to … — Я очень рекомендую эту книгу…
   

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3. An Example of a Review on the Book «The Secret History» by Donna Tratt

The Secret History is a powerful novel written by the American writer Donna Tartt. The story is set in New England and shows the life of students in some prestigious college. It is told by the fellow Richard Popen, who recently moved to the area from Calofornia. He happened to be aware of a terrible secret, which changed his life forever.

The Secret History is rich and detailed in plot and provide many layers for the reader to explore. The intricately constructed murder will hold your attention right up to the final page. The book is moving at times and amusing at others. The background of the book contains references to Ancient Greece, which you are sure to enjoy if you are interested in history.

As for the characters, Donna Tratt has managed to create different personalities from indulgent parents to light-hearted hippies. She is very convincing and depicted her characters very true to life. The contrast between the sophisticated ideas of the elite group of students and their contemporaries is done most skilfully.

In conclusion, I would like to note that the only reservation of the book is its length. It has more over 500 pages, so it is rather long. However, it’s difficult to put the book down. I highly recommend The Secret History  to everyone as the greatest achievement of this young novelist.

Model questions and answers

Review- Model question 1

TASK

INTRODUCTION

Make your review more interesting with personal comments

Mention the title, the type of the book/ play/ film/etc, the setting (when/where), the theme, the main characters, etc

Phrases you can use in the introduction:

• * This well-written/ informative / fascinatng/ thought-provoking book is…

• * The film/ book/ play/ etc. is set in….. / tells the story of…../ is based on…..

• * The film/ play starts …../ is directed by…../ is the sequel to…..

Comparing and contrasting

• *… is even better than …

• *… is (not) nearly as good as …

• *… is twice as good as …

• *… is the best I have ever seen / read / been to. in comparison with …

• *One of the strongest / weakest things about …

• *In contrast, … / On the other hand, …

REMEMBER:  A review is a special type of article written for publication in a magazine, newspaper, etc giving a brief description and evaluation of the film, book, play, TV/ radio programme, etc . It may be formal or semi-formal in style, depending on its intended readership, and is usually written using present tenses.

In the 2nd and 3rd Paragraph you :

• – include the main points of the plot ( without revealing the ending), and evaluate such features as the acting, writing style, directions, characters etc.

• – you can also add what you learnt, found out from the book, etc

Phrases you can use to in the 2nd and 3rd paragraph:

• * The plot revolves around …involves …/focuses on …/has an unexpected twist.

• * The story begins with …/unfolds / reaches a dramatic climax when …

 Evaluating various features:

• * The play/film/series has a strong/star-studded/mediocre cast.

• * The acting is moving/powerful/excellent/weak/disappointing/unconvincing.

• * The plot is gripping/dramatic/fascinating/suspense-filled/fast-moving. far-fetched/predictable/ confusing/dull /unimaginative.

• * The script/dialogue is touching/witty/hilarious/boring/mundane.

• * It is beautifully/brilliantly/sensitively written/directed.

CONCLUSION

• – include an overall assessment of the work and/or a recommendation, usually with justification

• – you may also be asked to give reasons why someone should see the film/ play or read the book, how it has influenced you, etc.

Phrases you can use to end the review

• *I would highly / strongly recommend …

• * I certainly wouldn’t recommend …

• * I strongly advise you (not) to …

• * Everyone should see / do / read this … immediately!

• * … is not to be missed!

• * You should give … a miss!

• * Don’t bother reading / seeing / going …

• * It is a classic of its kind/ It is sure to be a hit/ best -seller