Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer
Try for free
30 minutes trial then $15.00/month - No credit card required now
Go to Store
Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer
fastcrawler/twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer
Try for free
30 minutes trial then $15.00/month - No credit card required now
Extract up to 1,000 Twitter/X replies for just $0.01! With advanced sentiment and tone analysis, our Reply & Comment Scraper lets you sort replies by relevancy or likes effortlessly. Designed for speed and precision, it’s your ultimate tool for analyzing Twitter conversations efficiently.
You can access the Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer programmatically from your own applications by using the Apify API. You can choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "0.0",
5 "x-build-id": "yuUDPkxaRRSDf2ba9"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/fastcrawler~twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-fastcrawler-twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$ref": "#/components/schemas/inputSchema"
27 }
28 }
29 }
30 },
31 "parameters": [
32 {
33 "name": "token",
34 "in": "query",
35 "required": true,
36 "schema": {
37 "type": "string"
38 },
39 "description": "Enter your Apify token here"
40 }
41 ],
42 "responses": {
43 "200": {
44 "description": "OK"
45 }
46 }
47 }
48 },
49 "/acts/fastcrawler~twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer/runs": {
50 "post": {
51 "operationId": "runs-sync-fastcrawler-twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer",
52 "x-openai-isConsequential": false,
53 "summary": "Executes an Actor and returns information about the initiated run in response.",
54 "tags": [
55 "Run Actor"
56 ],
57 "requestBody": {
58 "required": true,
59 "content": {
60 "application/json": {
61 "schema": {
62 "$ref": "#/components/schemas/inputSchema"
63 }
64 }
65 }
66 },
67 "parameters": [
68 {
69 "name": "token",
70 "in": "query",
71 "required": true,
72 "schema": {
73 "type": "string"
74 },
75 "description": "Enter your Apify token here"
76 }
77 ],
78 "responses": {
79 "200": {
80 "description": "OK",
81 "content": {
82 "application/json": {
83 "schema": {
84 "$ref": "#/components/schemas/runsResponseSchema"
85 }
86 }
87 }
88 }
89 }
90 }
91 },
92 "/acts/fastcrawler~twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer/run-sync": {
93 "post": {
94 "operationId": "run-sync-fastcrawler-twitter-x-reply-comment-scraper-support-sentiment-tone-analyzer",
95 "x-openai-isConsequential": false,
96 "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
97 "tags": [
98 "Run Actor"
99 ],
100 "requestBody": {
101 "required": true,
102 "content": {
103 "application/json": {
104 "schema": {
105 "$ref": "#/components/schemas/inputSchema"
106 }
107 }
108 }
109 },
110 "parameters": [
111 {
112 "name": "token",
113 "in": "query",
114 "required": true,
115 "schema": {
116 "type": "string"
117 },
118 "description": "Enter your Apify token here"
119 }
120 ],
121 "responses": {
122 "200": {
123 "description": "OK"
124 }
125 }
126 }
127 }
128 },
129 "components": {
130 "schemas": {
131 "inputSchema": {
132 "type": "object",
133 "required": [
134 "tweetUrl",
135 "cookies"
136 ],
137 "properties": {
138 "tweetUrl": {
139 "title": "URL of the tweet",
140 "type": "string",
141 "description": "The URL of tweet you want to get the data from."
142 },
143 "sentimentAnalysis": {
144 "title": "sentiment analysis",
145 "type": "boolean",
146 "description": "Analyze the provided tweet and identify the primary \n\n **tone** (Positive, Negative, Neutral, Humorous, Sarcastic, Enthusiastic, Angry, Informative) \n\n **sentiment** (Positive, Negative, Neutral). \n\n **Note**: The analysis may take longer when checked."
147 },
148 "cookies": {
149 "title": "Cookies(please enter your twitter cookie)",
150 "type": "array",
151 "description": "Cookies are used to authorize the actor with twitter\n\n You can input multiple cookies, and when one cookie rate limit is set, it will automatically switch to another cookie to continue to capture data. \n\n Follow these steps to get the cookies:\n\n1. Install [Cookie-Editor](https://chromewebstore.google.com/detail/cookie-editor/hlkenndednhfkekhgcdicdfddnkalmdm) chrome extension\n2. Login to your twitter account\n3. Click on the extension and Export As 'Headers String' and export the twitter cookies\n4. Paste the copied contents here. \n\n [how-to-get-twitter-cookie](https://1-usd-promotion.com/how-to-get-twitter-cookie)",
152 "items": {
153 "type": "string"
154 }
155 },
156 "nextCursor": {
157 "title": "NextCursor",
158 "type": "string",
159 "description": "Cursor value to resume scraping from,You can get it from the last record in the returned data"
160 },
161 "rankingMode": {
162 "title": "RankingMode",
163 "enum": [
164 "Relevance",
165 "Recency",
166 "Likes"
167 ],
168 "type": "string",
169 "description": "Sort replies by",
170 "default": "Relevance"
171 },
172 "maxItems": {
173 "title": "Maximum number of items on output",
174 "minimum": 1,
175 "maximum": 100,
176 "type": "integer",
177 "description": "Maximum number of items that you want as output.",
178 "default": 10
179 }
180 }
181 },
182 "runsResponseSchema": {
183 "type": "object",
184 "properties": {
185 "data": {
186 "type": "object",
187 "properties": {
188 "id": {
189 "type": "string"
190 },
191 "actId": {
192 "type": "string"
193 },
194 "userId": {
195 "type": "string"
196 },
197 "startedAt": {
198 "type": "string",
199 "format": "date-time",
200 "example": "2025-01-08T00:00:00.000Z"
201 },
202 "finishedAt": {
203 "type": "string",
204 "format": "date-time",
205 "example": "2025-01-08T00:00:00.000Z"
206 },
207 "status": {
208 "type": "string",
209 "example": "READY"
210 },
211 "meta": {
212 "type": "object",
213 "properties": {
214 "origin": {
215 "type": "string",
216 "example": "API"
217 },
218 "userAgent": {
219 "type": "string"
220 }
221 }
222 },
223 "stats": {
224 "type": "object",
225 "properties": {
226 "inputBodyLen": {
227 "type": "integer",
228 "example": 2000
229 },
230 "rebootCount": {
231 "type": "integer",
232 "example": 0
233 },
234 "restartCount": {
235 "type": "integer",
236 "example": 0
237 },
238 "resurrectCount": {
239 "type": "integer",
240 "example": 0
241 },
242 "computeUnits": {
243 "type": "integer",
244 "example": 0
245 }
246 }
247 },
248 "options": {
249 "type": "object",
250 "properties": {
251 "build": {
252 "type": "string",
253 "example": "latest"
254 },
255 "timeoutSecs": {
256 "type": "integer",
257 "example": 300
258 },
259 "memoryMbytes": {
260 "type": "integer",
261 "example": 1024
262 },
263 "diskMbytes": {
264 "type": "integer",
265 "example": 2048
266 }
267 }
268 },
269 "buildId": {
270 "type": "string"
271 },
272 "defaultKeyValueStoreId": {
273 "type": "string"
274 },
275 "defaultDatasetId": {
276 "type": "string"
277 },
278 "defaultRequestQueueId": {
279 "type": "string"
280 },
281 "buildNumber": {
282 "type": "string",
283 "example": "1.0.0"
284 },
285 "containerUrl": {
286 "type": "string"
287 },
288 "usage": {
289 "type": "object",
290 "properties": {
291 "ACTOR_COMPUTE_UNITS": {
292 "type": "integer",
293 "example": 0
294 },
295 "DATASET_READS": {
296 "type": "integer",
297 "example": 0
298 },
299 "DATASET_WRITES": {
300 "type": "integer",
301 "example": 0
302 },
303 "KEY_VALUE_STORE_READS": {
304 "type": "integer",
305 "example": 0
306 },
307 "KEY_VALUE_STORE_WRITES": {
308 "type": "integer",
309 "example": 1
310 },
311 "KEY_VALUE_STORE_LISTS": {
312 "type": "integer",
313 "example": 0
314 },
315 "REQUEST_QUEUE_READS": {
316 "type": "integer",
317 "example": 0
318 },
319 "REQUEST_QUEUE_WRITES": {
320 "type": "integer",
321 "example": 0
322 },
323 "DATA_TRANSFER_INTERNAL_GBYTES": {
324 "type": "integer",
325 "example": 0
326 },
327 "DATA_TRANSFER_EXTERNAL_GBYTES": {
328 "type": "integer",
329 "example": 0
330 },
331 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
332 "type": "integer",
333 "example": 0
334 },
335 "PROXY_SERPS": {
336 "type": "integer",
337 "example": 0
338 }
339 }
340 },
341 "usageTotalUsd": {
342 "type": "number",
343 "example": 0.00005
344 },
345 "usageUsd": {
346 "type": "object",
347 "properties": {
348 "ACTOR_COMPUTE_UNITS": {
349 "type": "integer",
350 "example": 0
351 },
352 "DATASET_READS": {
353 "type": "integer",
354 "example": 0
355 },
356 "DATASET_WRITES": {
357 "type": "integer",
358 "example": 0
359 },
360 "KEY_VALUE_STORE_READS": {
361 "type": "integer",
362 "example": 0
363 },
364 "KEY_VALUE_STORE_WRITES": {
365 "type": "number",
366 "example": 0.00005
367 },
368 "KEY_VALUE_STORE_LISTS": {
369 "type": "integer",
370 "example": 0
371 },
372 "REQUEST_QUEUE_READS": {
373 "type": "integer",
374 "example": 0
375 },
376 "REQUEST_QUEUE_WRITES": {
377 "type": "integer",
378 "example": 0
379 },
380 "DATA_TRANSFER_INTERNAL_GBYTES": {
381 "type": "integer",
382 "example": 0
383 },
384 "DATA_TRANSFER_EXTERNAL_GBYTES": {
385 "type": "integer",
386 "example": 0
387 },
388 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
389 "type": "integer",
390 "example": 0
391 },
392 "PROXY_SERPS": {
393 "type": "integer",
394 "example": 0
395 }
396 }
397 }
398 }
399 }
400 }
401 }
402 }
403 }
404}Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients:
Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer API in Python
Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer API in JavaScript
Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer API through CLI
Twitter/X Reply Comment Scraper:Support Sentiment&Tone Analyzer API
Developer
fastcrawlerMaintained by Community
Actor Metrics
17 monthly users
-
7 stars
95% runs succeeded
2.7 hours response time
Created in Oct 2024
Modified 11 days ago
Categories
