Once you have heard about all the marketing techniques to improve your business, it is time to decide what strategie apply. You have been advised about the opinion of your clients is crucial for your web page´s views, it is time to decide how Artificial Intelligence would help you. Keep reading and find out!
It is very difficult to follow, identify and classify the comments, the emoticons and the consumers´reactions by hand using paper and pencil. Artificial Intelligence is crucial because it does all the work in an easy way.
There are APIs that can read the consumers´opinions in order to improve the marketing strategies so you can change , delete or even improve them so your business continue growing.
Sentiment analysis, commonly referred to as opinion mining, uses biometrics, computational linguistics, natural language processing, and text analysis to systematically locate, extract, and analyze affective states and subjective data. Sentiment analysis is frequently used in applications ranging from marketing to customer service to any industry. It is applied to voice of the customer materials including reviews and survey answers, internet and social media, and healthcare materials.
A basic task in sentiment analysis is classifying the polarity of a given text at the document, sentence or feature whether they are positive, negative or neutral. Advanced , beyond polarity sentiment classification looks , for instance, at emotional states such as enjoyment, anger, disgust, sadness, fear and surprise.
With recent developments made feasible by state-of-the-art Machine Learning and Deep Learning research, sentiment analysis is a particularly active topic of study in the field of Natural Language Processing (NLP). Sentiment analysis is primarily carried out by fine-tuning transformers because this approach has been demonstrated to work well with sequential data, such as text and speech, and scales remarkably on parallel processing resources.
Looking to perform Sentiment Analysis on a piece of written text or an audio or video file? Here are the top 3 Sentiment Analysis APIs to consider :
1- AssemblyAI´s Sentiment Analysis API: Released in November 2020, AssemblyAI´s Sentiment Analysis API has high accuracy for product teams and developers looking to perform Sentiment Analysis on audio or video streams, and is more accessible. Its Sentiment Analysis model leverages sentiment polarity to determine the probability that speech segments are positive, negative or neutral. In addition to Sentiment Analysis, AssemblyAI has a host of other Audio Intelligence APIs, including Entity Detection, Speaker Diarization, Content Moderation, Text Summarization and more.
2-Twinword Sentiment Analysis API: Twinword´s Sentiment Analysis API is a great option for simple textual analysis. The API´s basic package has different plans for different prices; for up to 500 words per month, with paid plans ranging from $19 to $250 per month depending on usage. The API applies scores and rations to mark a text as positive, negative or neutral. Rations are determined by comparing the overall scores of negative sentiments to psoitive sentiments and are applied on a -1 to 1 scale. In addition to Sentiment Analysis, Twinword also offers other forms of textual analysis such as Emotion Analysis, Text Similarity and Word Associations.
3-Zyla Opinion Analysis API: Zyla´s Opinion Analysis API performs Sentiment Analysis and more nuanced emotional, sentiment detection, such as emotions, relations and semantic roles on static texts. Keep in mind that the technology used to accurately identify these emotional complexities is still in its infancy, so use more advanced features with caution. The Pure Sentiment Analysis API assigns sentiments detected in either entities or keywords both a magnitude and score help users better understand chosen text.
Also, be sure to review available documentation and any change that indicate how often the Sentiment Analysis feature, and others, are updated. Zyla´s Opinion Analysis API based on the latest research and insights are most likely to ensure continued accuracy and ease of use,