[initial] Gosentiwordnet v2 release

.gitignore

@@ -0,0 +1,3 @@
+coverage.txt
+coverage.out
+coverage.html

.travis.yml

@@ -0,0 +1,10 @@
+language: go
+go:
+  - 1.14.x
+
+script:
+  - go test -v -coverprofile=coverage.txt -covermode=count
+
+after_success:
+  - bash <(curl -s https://codecov.io/bash)
+  - rm -rf coverage.txt

FUNDING.yml

@@ -0,0 +1,7 @@
+# These are supported funding model platforms
+
+github: [dinopuguh] # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2]
+patreon: # Replace with a single Patreon username
+open_collective: # Replace with a single Open Collective username
+ko_fi: # Replace with a single Ko-fi username
+tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel

README.md

@@ -1 +1,60 @@
-go-sentiwordnet
+# 💬 GoSentiwordnet
+
+Sentiment analyzer using [sentiwordnet](https://github.com/aesuli/SentiWordNet) lexicon in Go. This library produce sentiment score for each word, including positive, negative, and objective score. 
+
+## ⚙ Installation
+
+First of all, [download](https://golang.org/dl/) and install Go `1.14` or higher is required.
+
+Install this library using the [`go get`](https://golang.org/cmd/go/#hdr-Add_dependencies_to_current_module_and_install_them) command:
+
+```bash
+$ go get github.com/dinopuguh/gosentiwordnet
+```
+
+
+
+## ⚡ Quickstart
+
+```go
+package main
+
+import (
+    "fmt"
+
+    goswn "github.com/dinopuguh/gosentiwordnet"
+)
+
+func main() {
+    sa := goswn.New()
+
+    scores, exist := sa.GetSentimentScore("love", "v", "2")
+    if exist {
+        fmt.Println("💬 Sentiment score:", scores) // => 💬 Sentiment score: {1 0 0}
+    }
+}
+```
+
+The `GetSentimentScore` required 3 parameters(word, pos-tag, and word usage):
+
+1. **Word**: the word want to process
+2. **POS tag**: part-of-speech tag of the word
+3. **Word usage**: 1 for most common usage and a higher number would indicate lesser common usages
+
+
+
+## 👍 Contributing
+
+If you want to say **thank you** and/or support the active development of `Gosentiwordnet`:
+
+1. Add a [GitHub Star](https://github.com/dinopuguh/gosentiwordnet/stargazers) to the project.
+2. Write a review or tutorial on [Medium](https://medium.com/), [Dev.to](https://dev.to/) or personal blog.
+3. Be a part of our [sponsors](https://github.com/sponsors/dinopuguh) to support this project.
+
+
+
+## 💻 Contributors
+
+- Dino Puguh (initial works)
+
+Open for any pull requests to develop this project.

example/main.go

@@ -0,0 +1,32 @@
+package main
+
+import (
+	"fmt"
+
+	goswn "github.com/dinopuguh/gosentiwordnet"
+)
+
+// Token represent the required parameter for using gosentiwordnet
+type Token struct {
+	Word   string // the word want to process
+	PosTag string // part-of-speech tag of word
+	Usage  string // word usage (1 for most common usage and a higher number would indicate lesser common usages)
+}
+
+func main() {
+	sa := goswn.New()
+
+	tokens := []Token{
+		Token{Word: "love", PosTag: "v", Usage: "2"},
+		Token{Word: "neat", PosTag: "a", Usage: "4"},
+		Token{Word: "overacting", PosTag: "n", Usage: "1"},
+	}
+
+	for _, token := range tokens {
+		scores, exist := sa.GetSentimentScore(token.Word, token.PosTag, token.Usage)
+		if exist {
+			fmt.Printf("💬 Sentiment score of %s: %v\n", token.Word, scores)
+			// 💬 Sentiment score: {positive_score negative_score objective_score}
+		}
+	}
+}

go.mod

@@ -0,0 +1,5 @@
+module github.com/dinopuguh/gosentiwordnet
+
+go 1.14
+
+require github.com/stretchr/testify v1.6.1

go.sum

@@ -0,0 +1,10 @@
+github.com/davecgh/go-spew v1.1.0 h1:ZDRjVQ15GmhC3fiQ8ni8+OwkZQO4DARzQgrnXU1Liz8=
+github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
+github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
+github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
+github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
+github.com/stretchr/testify v1.6.1 h1:hDPOHmpOpP40lSULcqw7IrRb/u7w6RpDC9399XyoNd0=
+github.com/stretchr/testify v1.6.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
+gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
+gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c h1:dUUwHk2QECo/6vqA44rthZ8ie2QXMNeKRTHCNY2nXvo=
+gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=

gosentiwordnet.go

@@ -13,10 +13,13 @@ import (
 
 const sentiWordnetAssetName = "rawdata/SentiWordNet_3.0.0.txt"
 
+// SentimentAnalyzer represent the sentiment analyzer with sentiwordnet lexicon
 type SentimentAnalyzer struct {
 	Lexicon map[string]Sentiment
 }
 
+// Sentiment reprensent sentiment score for each word
+// containing positive, negative and objective
 type Sentiment struct {
 	Positive  float64
 	Negative  float64
@@ -56,13 +59,12 @@ func (sa *SentimentAnalyzer) generateLexicon() {
 
 		line++
 	}
-
-	if err := scanner.Err(); err != nil {
-		log.Fatal(err.Error())
-	}
 }
 
-func (sa *SentimentAnalyzer) GetSentimentScore(word string, posTag string, usage string) (bool, Sentiment) {
+// GetSentimentScore count the sentiment score of word based on POS tag and the word usage.
+// POS tag: part-of-speech tag of word
+// Word usage: 1 for most common usage and a higher number would indicate lesser common usages
+func (sa *SentimentAnalyzer) GetSentimentScore(word string, posTag string, usage string) (Sentiment, bool) {
 	var result Sentiment
 
 	posTag = "(" + posTag + ")"
@@ -78,10 +80,11 @@ func (sa *SentimentAnalyzer) GetSentimentScore(word string, posTag string, usage
 		}
 	}
 
-	return match, result
+	return result, match
 }
 
-func NewGoSentiwordnet() *SentimentAnalyzer {
+// New generate the sentiment analyzer with sentiwordnet lexicon
+func New() *SentimentAnalyzer {
 	var sa SentimentAnalyzer
 
 	sa.generateLexicon()

gosentiwordnet_test.go

@@ -0,0 +1,34 @@
+package gosentiwordnet_test
+
+import (
+	"testing"
+
+	"github.com/dinopuguh/gosentiwordnet"
+	"github.com/stretchr/testify/assert"
+)
+
+type SentimentTestCase struct {
+	Word   string
+	PosTag string
+	Usage  string
+	Scores gosentiwordnet.Sentiment
+}
+
+func generateTestCases() []SentimentTestCase {
+	return []SentimentTestCase{
+		SentimentTestCase{Word: "love", PosTag: "v", Usage: "2", Scores: gosentiwordnet.Sentiment{Positive: 1, Negative: 0, Objective: 0}},
+		SentimentTestCase{Word: "neat", PosTag: "a", Usage: "4", Scores: gosentiwordnet.Sentiment{Positive: 0.625, Negative: 0, Objective: 0.375}},
+		SentimentTestCase{Word: "overacting", PosTag: "n", Usage: "1", Scores: gosentiwordnet.Sentiment{Positive: 0, Negative: 0.875, Objective: 0.125}},
+		SentimentTestCase{Word: "finely", PosTag: "r", Usage: "2", Scores: gosentiwordnet.Sentiment{Positive: 0.625, Negative: 0, Objective: 0.375}},
+	}
+}
+
+func TestSentimentAnalysis(t *testing.T) {
+	sa := gosentiwordnet.New()
+	for _, testCase := range generateTestCases() {
+		scores, match := sa.GetSentimentScore(testCase.Word, testCase.PosTag, testCase.Usage)
+		if match {
+			assert.Equalf(t, testCase.Scores, scores, testCase.Word)
+		}
+	}
+}