Baidu AI interface and Golang: implement sentiment analysis and make applications more intelligent

Baidu AI interface and Golang: implementing emotional analysis and making applications more intelligent

Introduction:
In recent years, with the rapid development of artificial intelligence, emotional analysis As one of the important applications of natural language processing, it is widely used in social media monitoring, public opinion analysis, emotion recognition and other fields. Baidu AI interface provides powerful sentiment analysis capabilities. Combined with the efficient performance of Golang language, it can achieve fast and accurate sentiment analysis and add intelligent functions to applications. This article will introduce how to use Baidu AI interface and Golang language to implement sentiment analysis, and give code examples.

1. Overview of Baidu AI interface
Baidu AI interface is a series of artificial intelligence capabilities provided by Baidu Intelligent Cloud, including sentiment analysis, speech recognition, image recognition, etc. This article will focus on the use of sentiment analysis interfaces.

Baidu sentiment analysis interface is a technology that analyzes text content to determine its emotional tendency. It can make positive, negative and neutral emotional judgments on texts and give corresponding emotional probabilities.

2. Characteristics of Golang language
Golang is a modern and efficient programming language with strong concurrency performance, static type checking, garbage collection and other characteristics. It is suitable for developing high-performance applications.

3. Use Baidu AI interface to implement sentiment analysis

1. Building development environment
   First, you need to install the Golang language environment and apply for an API Key on Baidu Smart Cloud. Use To call the sentiment analysis interface.
2. Introduce necessary libraries
   In Golang, you can use the net/http library to perform HTTP request operations. This library needs to be introduced in the code.

import (
    "net/http"
    "io/ioutil"
    "encoding/json"
)

3. Send a request and parse the returned results
   Use the HTTP POST method to send a request to the Baidu AI interface, and pass the text that needs sentiment analysis as a parameter. Parse the returned results.

func SentimentAnalysis(text string) (string, error) {
    url := "https://aip.baidubce.com/rpc/2.0/nlp/v1/sentiment_classify"
    
    // 拼接请求参数
    data := map[string]interface{}{
        "text": text,
    }

    jsonStr, _ := json.Marshal(data)

    req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonStr))
    if err != nil {
        return "", err
    }

    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("Charset", "UTF-8")

    // 设置API Key
    q := req.URL.Query()
    q.Add("access_token", "YOUR_API_KEY")
    req.URL.RawQuery = q.Encode()

    client := http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        return "", err
    }

    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)

    type Result struct {
        Item struct {
            PositiveProb float64 `json:"positive_prob"`
            NegativeProb float64 `json:"negative_prob"`
            Confidence   float64 `json:"confidence"`
        } `json:"items"`
    }

    var result Result
    err = json.Unmarshal(body, &result)
    if err != nil {
        return "", err
    }

    // 根据情感概率判断情感倾向
    if result.Item.PositiveProb > result.Item.NegativeProb {
        return "positive", nil
    } else if result.Item.PositiveProb < result.Item.NegativeProb {
        return "negative", nil
    } else {
        return "neutral", nil
    }
}

4. Sample code and running results
The following is a sample code that implements the sentiment analysis function in the application.

func main() {
    text := "这家餐馆的服务非常好，菜品也很美味。" 

    result, err := SentimentAnalysis(text)
    if err != nil {
        fmt.Println("Error:", err)
    } else {
        fmt.Println("Sentiment Analysis Result:", result)
    }
}

Running results:

Sentiment Analysis Result: positive

5. Summary
This article introduces how to use Baidu AI interface and Golang language to implement sentiment analysis, and gives code examples. In this way, we can take advantage of the powerful functions provided by Baidu AI interface to add intelligent sentiment analysis capabilities to applications. I hope this article helps you understand and apply sentiment analysis. If you have other needs or more questions, please consult the documentation of Baidu AI interface for in-depth study.

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