我们提供TikTok用户和”料子“筛活服务和工具，We provide TikTok users filter service and software.

在使用我们的工具采集大量的TikTok用户ID和资料之后：我们提供批量采集TikTok竞争对手和指定账号粉丝的工具和服务，We provide TikTok account followers extraction software & service；

或者通过我们的工具采集到指定领域的海外抖音达人资料之后：(3)我们提供批量采集 TikTok 达人资料的服务和工具，技术路径和示例代码。

出海营销人员可以通过我们的工具批量关注这些TikTok用户 - 我们提供批量自动关注TikTok大V和竞争对手的粉丝的工具和服务，为什么通过批量关注获得”回粉“能够迅速为自己的海外抖音账号涨粉？或者批量打招呼工具：我们提供 TikTok 批量打招呼的服务和工具实现快速涨粉，We help you bulk greeting TikTok users to grow followers， 从而通过”回粉“将竞争对手的粉丝变成自己账号的粉丝；

当然，也可以用我们的自动化触达工具开始给这些用户群发消息：(2)我们提供 TikTok 批量发送 DM 私信的服务和工具，海外抖音批量发送消息的技术指南！

但是，在尝试批量触达这些潜在客户之前，一定要对采集的TikTok用户资料进行“筛活”。原因很简单，通过工具采集的TikTok用户里面，有大量的机器粉，死号或者inactive不活跃用户。在针对这些用户做任何营销推广之前，我们|飞机号: t.me/bulk006|建议首先要完成”精筛“甚至”二筛“工作，剔除掉没有价值的用户账号，然后再给这些竞争对手的粉丝直接发送推广信息，并引导到WhatsApp或者Telegram私域，实现实际转化。

那么，TikTok筛号是怎样实现的呢？

我们提供自动筛选 TikTok 活跃用户的工具：删除非活跃、机器人和死号账户

从采集的 TikTok 用户列表中删除非活跃账号、机器人账号和死号账户，是在TikTok平台上触达潜在客户、拉新获客的关键步骤之一。以下是使用各种技术和工具实现此目的的分步指南：

技术要求：

1. TikTok API 密钥：您需要一个 TikTok API 密钥来访问 TikTok API。

2. 编程语言：您可以使用任何支持 HTTP 请求和 JSON 解析的编程语言，例如 Python、JavaScript 或 Ruby。

3. 网页爬虫库：您需要一个网页爬虫库来从 TikTok 的网页中提取数据。对于 Python，可以使用 BeautifulSoup 和 Requests。

4. 自然语言处理 (NLP) 库：您需要一个 NLP 库来分析用户配置文件和检测可疑活动。对于 Python，可以使用 NLTK 或 spaCy。

5. 数据库或数据存储：您需要一个数据库或数据存储解决方案来存储筛选后的用户列表。

步骤 1：收集用户数据

• 使用 TikTok API 收集用户数据，例如用户名、头像、bio 和粉丝数。

• 您可以使用 Python 的 requests 库来发送 GET 请求到 TikTok API：

步骤 2：分析用户配置文件

• 分析用户的头像、bio 和用户名来检测可疑活动。

• 使用 NLP 库来分析 bio 并检测可能指示机器人或非活跃账户的关键词。

• 例如，您可以使用 NLTK 在 Python 中对 bio 进行分词并检测关键词：

步骤 3：检查粉丝和关注数

• 检查用户的粉丝和关注数来检测可疑活动。

• 使用 TikTok API 来检索用户的粉丝和关注数：

步骤 4：检查账户年龄和活动

• 检查用户的账户年龄和活动来检测非活跃账户。

• 使用 TikTok API 来检索用户的创建日期和最后活动日期：

步骤 5：筛选出非活跃、机器人和死号账户

• 使用收集的数据来筛选出非活跃、机器人和死号账户。

• 创建一个评分卡来评估每个用户基于收集的数据。

• 例如，您可以使用以下评分卡：

步骤 6：存储筛选后的用户列表

• 将筛选后的用户列表存储在数据库或数据存储解决方案中。

• 例如，您可以使用 CSV 文件来存储筛选后的用户列表：

示例代码：

以下是一个示例代码，演示了筛选过程：

注意： 这只是一个示例代码，您需要根据具体需求修改它以适应您的采集和筛选目标，并处理错误。此外，还需要注意的是，调用 TikTok API 一定会违反平台的服务条款和 API 使用政策。因此，我们|飞机号: t.me/bulk006|建议出海企业，如无技术基础，可直接购买我们的“筛活”服务。

Automatically Filtering TikTok Users: Removing Inactive, Bot, and Dead Accounts

Filtering out inactive, bot, and dead accounts from a list of TikTok users is crucial to maintain a healthy and engaged user base. Here's a step-by-step guide to help you achieve this using various techniques and tools:

Technical Requirements:

1. TikTok API Key: You'll need a TikTok API key to access the TikTok API.

2. Programming Language: You can use any programming language that supports HTTP requests and JSON parsing, such as Python, JavaScript, or Ruby.

3. Web Scraping Library: You'll need a web scraping library to extract data from TikTok's web pages. For Python, you can use BeautifulSoup and Requests.

4. Natural Language Processing (NLP) Library: You'll need an NLP library to analyze user profiles and detect suspicious activity. For Python, you can use NLTK or spaCy.

5. Database or Data Storage: You'll need a database or data storage solution to store the filtered user list.

Step 1: Collect User Data

• Use the TikTok API to collect user data, such as username, profile picture, bio, and followers count.

• You can use the requests library in Python to send a GET request to the TikTok API:

import requestsapi_key = "YOUR_API_KEY"username = "TARGET_USERNAME"url = f"https://api.tiktok.com/aweme/v1/user/{username}?access_token={api_key}"response = requests.get(url)

user_data = response.json()

Step 2: Analyze User Profile

• Analyze the user's profile picture, bio, and username to detect suspicious activity.

• Use an NLP library to analyze the bio and detect keywords that may indicate a bot or inactive account.

• For example, you can use NLTK in Python to tokenize the bio and detect keywords:

import nltkfrom nltk.tokenize import word_tokenizebio = user_data["bio"]tokens = word_tokenize(bio)suspicious_keywords = ["bot", "auto", "follow", "like", "comment"]if any(keyword in tokens for keyword in suspicious_keywords):    print("Suspicious bio detected")

Step 3: Check Followers and Following Count

• Check the user's followers and following count to detect suspicious activity.

• Use the TikTok API to retrieve the user's followers and following count:

url = f"https://api.tiktok.com/aweme/v1/user/{username}/followers?access_token={api_key}"response = requests.get(url)followers_count = response.json()["count"]url = f"https://api.tiktok.com/aweme/v1/user/{username}/following?access_token={api_key}"response = requests.get(url)following_count = response.json()["count"]if followers_count < 10 or following_count < 10:    print("Suspicious followers or following count detected")

Step 4: Check Account Age and Activity

• Check the user's account age and activity to detect inactive accounts.

• Use the TikTok API to retrieve the user's creation date and last active date:

url = f"https://api.tiktok.com/aweme/v1/user/{username}?access_token={api_key}"response = requests.get(url)creation_date = response.json()["created_at"]last_active_date = response.json()["last_active_at"]if (datetime.now() - creation_date).days > 30 and (datetime.now() - last_active_date).days > 30:    print("Inactive account detected")

Step 5: Filter Out Inactive, Bot, and Dead Accounts

• Use the collected data to filter out inactive, bot, and dead accounts.

• Create a scorecard to evaluate each user based on the collected data.

• For example, you can use the following scorecard:

score = 0if suspicious_bio:    score -= 2if followers_count < 10 or following_count < 10:    score -= 1if (datetime.now() - creation_date).days > 30 and (datetime.now() - last_active_date).days > 30:    score -= 2if score < -3:    print("Account filtered out")

Step 6: Store the Filtered User List

• Store the filtered user list in a database or data storage solution.

• For example, you can use a CSV file to store the filtered user list:

import csvfiltered_users = []# ... (rest of the code)with open("filtered_users.csv", "w", newline="") as csvfile:    writer = csv.writer(csvfile)    writer.writerow(["Username", "Score"])    for user in filtered_users:        writer.writerow([user["username"], user["score"]])

Example Code:

Here's an example code that demonstrates the filtering process:

import requestsimport nltkfrom nltk.tokenize import word_tokenizeimport datetimeimport csvapi_key = "YOUR_API_KEY"username = "TARGET_USERNAME"# Step 1: Collect user dataurl = f"https://api.tiktok.com/aweme/v1/user/{username}?access_token={api_key}"response = requests.get(url)
user_data = response.json()# Step 2: Analyze user profilebio = user_data["bio"]tokens = word_tokenize(bio)suspicious_keywords = ["bot", "auto", "follow", "like", "comment"]suspicious_bio = any(keyword in tokens for keyword in suspicious_keywords)# Step 3: Check followers and following counturl = f"https://api.tiktok.com/aweme/v1/user/{username}/followers?access_token={api_key}"response = requests.get(url)followers_count = response.json()["count"]url = f"https://api.tiktok.com/aweme/v1/user/{username}/following?access_token={api_key}"response = requests.get(url)following_count = response.json()["count"]# Step 4: Check account age and activitycreation_date = datetime.datetime.fromtimestamp(user_data["created_at"])last_active_date = datetime.datetime.fromtimestamp(user_data["last_active_at"])# Step 5: Filter out inactive, bot, and dead accountsscore = 0if suspicious_bio:    score -= 2if followers_count < 10 or following_count < 10:    score -= 1if (datetime.datetime.now() - creation_date).days > 30 and (datetime.datetime.now() - last_active_date).days > 30:    score -= 2if score < -3:    print("Account filtered out")# Step 6: Store the filtered user listfiltered_users = []# ... (rest of the code)with open("filtered_users.csv", "w", newline="") as csvfile:    writer = csv.writer(csvfile)    writer.writerow(["Username", "Score"])    for user in filtered_users:        writer.writerow([user["username"], user["score"]])

Note: This is just an example code and may not work as-is. You'll need to modify it to suit your specific requirements and handle errors. Additionally, be aware of TikTok's terms of service and API usage policies.

如何联系此批量采集和群发工具的开发者及服务商：如需Telegram, WhatsApp, TikTok及全网和17个主流SNS社媒平台海量采集工具、筛活、及强制拉群、群发DM服务，可加此软件开发者的飞机号了解更多，他们的Telegram账号是：t.me/NomieEd（Eng pls）

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