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5 results for “Vkontakte”
Anonymized Graph Data with Friend Connections of 189505 VKontakte Users
<p>The dataset contains anonymized graph data with friend connections of 189505 VKontakte users. The dataset was used in <a href="http://github.com/filipp134/vk_bot_detection">this</a> Github project on the detection of social bots on VKontakte. The script which was used for the collection of the dataset is <a href="https://github.com/filipp134/vk_bot_detection/blob/main/Collecting%20datasets%20and%20merging%20them%20into%20one/collect_graph_data.py">here</a>.</p> <p>The dataset was collected in the following 2 steps by using the official <a href="https://dev.vk.com/api/getting-started">VKontakte API</a>:</p> <p>1. Friend connections of 11766 VKontakte users, who had 177739 unique friends, were collected.</p> <p>2. Friend connections of these 177739 users were collected. </p> <p>The dataset is in JSON format and is quite heavy: 424.5 MB.</p> <p> </p>
Global Vkontakte User Dataset
<p>Online Social Networks enable individuals to present a version of themselves to their immediate social circle and beyond. Those presentations express cultural factors such as an individuals gender, location, political, philosophical and religions values. Obtaining such data; however, is often challenging on the aggregate level as it typically involves negotiations with private entities and ownership restrictions. This study presents a dataset of 563,615,517 user accounts from the platform Vkontakte, an online social network collected in June of 2020. Vkontakte is a social media platform similar in nature to Facebook that allows individuals to connect with other users, communicate with them through public and private messages, as well as create public personas of themselves. This dataset can be used to perform cross-national and cross-cultural analyses of online culture from a large proportion of the world.</p>
Socio-demographic portrait and demographic values of pro-natalists and anti-natalists in Russia: assessment based on data from the social network VKontakte
<p>The dataset contains data from personal profiles of social network users VKontakte - socio-demographic characteristics (gender, age, date of birth, marital status, country and city of residence) and indicators of demographic values (“the main thing in life”, attitude to alcohol, attitude to smoking, pronatalist or anti-natalist), as well as a number of other indicators - religious and political beliefs,<br> "the main thing in people." Initially, as a selection criterion, the authors used belonging user to the relevant communities (groups) of the VKontakte social network, sharing different family and reproductive values (to be a parent, to give birth child, start a family or profess the values of childfree philosophy). For example, persons who were members of groups devoted to "childfree" values were assigned the status "anti-natalist". And individuals in groups devoted to issues of childbirth and family values, parenthood, were assigned the status of "pronatalist". For example, groups with the names "GOOD PARENTS" (https://vk.com/club52388302) and "MOM: Development, Family, Children" (https://vk.com/club69716165) are pronatalist, and groups "The TRUTH about Childfree (Childfree)" (https://vk.com/club58565280) and "Overheard Childfree" (https://vk.com/club69265846) - to anti-natalist ones. The authors extracted comments of users of these two types of groups in the social network VKontakte, applying methods of extraction (parsing) of data from social networks using VK API. Organized open access to databases compiled by us from hundreds<br> thousand comments from users of dozens of groups of two types in more than one and a half decades [Kalabikhina &amp; Banin, 2020; Kalabikhina &amp; Banin, 2021]. Further, the authors linked the data of their personal data to users from these groups.<br> questionnaires. At the second stage, the resulting sample was additionally corrected - in it only those persons who filled in the field "The main thing in life" in the personal questionnaire on VKontakte to determine priority values for users with different types of reproductive behavior. Include in the analysis only those users who answered the question from personal questionnaire on VKontakte about what is most important for them in life, allows reduce the risk of "bots" getting into the sample. We believe that in the questionnaires of bots such fields as "The main thing in life", "The main thing in people" will not be filled in, the indication of this<br> information in the personal profile testifies in favor of the fact that the account is really belongs to a real person. At this stage, the sample included 754,315 users. Additionally, we limited the sample according to the age indicated in the questionnaire. We excluded from the sample users who indicated their age of 80 years and older. We we believe that this is an indirect sign by which it is possible to identify accounts with inaccurate information. The final sample after the introduced restrictions was 377,786 people, it includes users of the social network VKontakte, consisting of groups of anti-natalists and pro-natalists who filled in the information section about themselves item "The main thing in life" minus persons who indicated in the questionnaire that they are over 80 years old.</p>
Familiist (pro-natalist) communities in the social network VKontakte
<p>The database contains an upload of text comments in Russian from the social networkVkontakte in <strong>.csv format (UTF-8 encoding). </strong>Comments are collected from communities, which discuss pregnancy, childhood, motherhood, paternity, etc. The unloading contains comments under the posts with which the interaction took place. The absolute amount of likes was used as a criterion, (comments were collected where the number of likes is greater than or equal to 5). The text data was processed (stemmization and lemmatization). The data are suitable for thematic analysis (e.g. LDA - Latent Dirichlet Allocation), for modelling the graph structure of communities (the link_comment variable contains a unique identifier of the post, link_author contains a unique user identifier), for analysis of the tonalities of statements and forming a dictionary of demographic connotation. </p> <p>Sample Information:</p> <p>- Number of communities 38 </p> <p>- Content type of communities: communities in which users are mainly positive about the birth of children, motherhood, parenthood and own family are selected. But users (communities) with anti-familistic biases may be encountered. </p> <p>- Only comments with the number of likes >= 5 are collected </p> <p>- Comments are collected only from communities (the list of communities below) discussing issues related to childhood, motherhood, pregnancy, etc. </p> <p>- A sample of communities on average contains 309 thousand subscribers (maximum value - 1,482,303, minimum value - 72,570, total number of subscribers excluding intersections - 11,743 295) </p> <p>- The sample of comments contains 112,900 user comments </p> <p>Sample Structure: </p> <p>link_author - link to the author of the comment in the form of https://vk.com/*author identificator* </p> <p>gender of author (F - female, M - male, NaN - no data) </p> <p>link_comment - link to comment in the form of https://vk.com/* post identificatior on a *community wall*?reply=*comment id * </p> <p>date_time - date and time of publication (format “YYYY-MM-DD HH:MM:SS”) </p> <p>text - raw comment text </p> <p>likes - number of likes the comment has </p> <p>text_prep - processed text (punctuation marks removed, words brought down to lowercase) </p> <p>text_stem - processed text (based on the text_prep column stemmization using SnowBallstemmer (“Russian”) of the nltk library) is performed </p> <p>text_sw - processed text (based on the text_prep column stop words are deleted using word_tokenize (text) of the nltk library) </p> <p>text_lemm - processed text (lemmatization using mystem.lemmatize (text) of pymystem3 library is performed based on the text_prep column) </p> <p>List of communities (38 communities):</p> <p>https://vk.com/club52388302</p> <p>https://vk.com/club34677924</p> <p>https://vk.com/club99834596</p> <p>https://vk.com/club170234932</p> <p>https://vk.com/club20199180</p> <p>https://vk.com/club118030893</p> <p>https://vk.com/club14395935</p> <p>https://vk.com/club100104267</p> <p>https://vk.com/club181526404</p> <p>https://vk.com/club35095382</p> <p>https://vk.com/club58530763</p> <p>https://vk.com/club69716165</p> <p>https://vk.com/club29746763</p> <p>https://vk.com/club78865067</p> <p>https://vk.com/club20709572</p> <p>https://vk.com/club93466205</p> <p>https://vk.com/club61700163</p> <p>https://vk.com/club91423062</p> <p>https://vk.com/club69285929</p> <p>https://vk.com/club104012302</p> <p>https://vk.com/club20622108</p> <p>https://vk.com/club86333616</p> <p>https://vk.com/club24765</p> <p>https://vk.com/club87169444</p> <p>https://vk.com/club86688308</p> <p>https://vk.com/club93776129</p> <p>https://vk.com/club47207301</p> <p>https://vk.com/club39873171</p> <p>https://vk.com/club59224150</p> <p>https://vk.com/club7430494</p> <p>https://vk.com/club37739956</p> <p>https://vk.com/club59701255</p> <p>https://vk.com/club27427277</p> <p>https://vk.com/club126238531</p> <p>https://vk.com/club127678644</p> <p>https://vk.com/club57782234</p> <p>https://vk.com/club51314884</p> <p>https://vk.com/club134261249</p>
Vkontakte Values Dataset
<p>Dataset for Value Orientation and Network Power: A Cross-National Study on Vkontakte</p>
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