There are three “strange” tiers where price increases with the volume. Language SupportĬombined, all services we compared support 23 languages, while a single service supporting 17 languages at most (Microsoft and Repustate).
It is not clear if it is used in other models implicitly. Surprisingly, only Meaning Cloud provides explicit irony detection. However, it is not clear if it is augmented with the cross-sentence anaphora resolution, which should be especially important for conversational texts.Īdditionally, Aylien and Meaning Cloud provide sentiment subjectivity score, measuring how subjective is the writer opinion. This is supported by Google Cloud Natural Language. We have found aspect-based sentiment in Aylien, Meaning Cloud and Repustate, with different domain models available at each of the services.Īnother way to get more details is to perform entity extraction and then to analyse sentiment towards each of the entities mentioned in the sentence. An example is a restaurant review, which may combine sentiment towards service, meals, and prices in one sentence.Īspect-based models are always domain specific. One case is when the subject can be evaluated along different dimensions or aspects. Sometimes sentence-level sentiment score is not enough. Some other services allow for adding custom sentiment dictionaries (list of words with attached sentiment polarity scores), which we did not count as custom models here. IBM Watson, Meaning Cloud and Salesforce Einstein enable building custom models to account for specific slang or language used in some specific domain. Google Cloud’s sentiment magnitude may refer to the same problem, if it may be high for neutral sentiment (needs testing). Meaning Cloud solves that by introducing the sentiment agreement score. One important distinction is the Mixed sentiment, which may be indicated by a particular label in the latter approach but typically cannot be expressed in the former. Different services provide labels for a different number of steps on this scale. The alternative approach is to return a set of sentiment labels with a confidence score attached to each label. Most of the services represent it by a sentiment score within some range between negative and positive ( or ). Sentiment polarity is the main metric of sentiment. Here we focus on the services that analyze the expressed attitude towards an object, as opposed to the Emotion Analysis, which evaluates the emotional state of the writer. Sentiment analysis aims to determine the attitude of a speaker, writer, or other subject with respect to some topic or the overall contextual polarity or emotional reaction to a document, interaction, or event.
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You may find the full list of services we compared together with links and some other details in the Slideshare deck. Microsoft Cognitive Services Text Analytics.Social Sentiment Analysis by nlu at Algorithmia.Sentiment Analysis by nlu at Algorithmia.Sentiment Analysis by mtman at Algorithmia.We evaluate services with public API and public pricing, with two exceptions: Salesforce Einstein, which bundles with Salesforce subscription and TheSay PreCeive, which does not have public pricing. We have compared 15 Cloud Sentiment Analysis services with pre-built models, provided via public APIs.įour of them are hosted on the Algorithmia marketplace. Slides from this report are also available on Slideshare. The prices vary from $1 to $99 per 10,000 API calls across base tiers of different vendors.
We compare 15 Cloud Sentiment Analysis services, which support a total of 23 languages. In this overview, we share some insights we got during the integration. Recently we have integrated many Sentiment Analysis services. Intento simplifies it by providing the same interface to all those services.
All these make the comparison and evaluation a must.Īt the same time, the evaluation is expensive and cumbersome because of the vast difference in the service APIs. Cloud Sentiment Analysis - Vendor Overview IntroductionĬognitive AI is a unique market, where seemingly similar services are available at up to 100x different prices.Īlso, the quality of service depends on how data used by the vendor to train its models is similar to the data to be processed.
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