Building A Corporate Corpus For Threads Constitution (2021)

Abstract: In this paper we describe the process of build-ing a corporate corpus that will be used as a ref-erence for modelling and computing threadsfrom conversations generated using commu-nication and collaboration tools. The overallgoal of the reconstruction of threads is to beable to provide value to the collorator in var-ious use cases, such as higlighting the impor-tant parts of a running discussion, reviewingthe upcoming commitments or deadlines, etc. Since, to our knowledge, there is no avail-able corporate corpus for the French languagewhich could allow us to address this prob-lem of thread constitution, we present here amethod for building such corpora includingdifferent aspects and steps which allowed thecreation of a pipeline to pseudo-anonymisedata. Such a pipeline is a response to theconstraints induced by the General Data Pro-tection Regulation GDPR in Europe and thecompliance to the secrecy of correspondence.

## introduction computer mediated communication (cmc) tools are used to produce and exchange an enormous amount of contents such as emails, chats and fora. but these contents are usually little or not structured, which makes the automatic extraction of knowledge difficult. in this paper, we tackle the issue of the constitution of threads in conversations within a specific company. this problem strongly relates to that of conversations disentanglement which have been addressed in several research works. @xcite computed message similarity using language representation to address this problem. such problems requires the existence of a corpus to analyse. it is why @xcite have built a large-scale corpus for conversations disentanglement, also the en-ron corpus was created by @xcite for email classification research. in the same way @xcite built the comere corpus for french and @xcite created the avocado research email collection. more recently @xcite built the webis gmane email corpus from the archive of gmane mailing list. among these corpora, some are from enron and avocado companies, but they are in english and their content have specific contexts different from those of the company of which we will create a corpus. those that are in french have very few emails around 2030 (comere) or are mailing list conversations with themes and context that do not fit with corporate conversations. one approach could be transfer learning, @xcite use multilingual transfer learning for question answering problem. but the context of a company is very circumscribed and specific. in this paper we describe a method for building a corporate corpus based on emails data. we specifically address the process of collecting, preprocessing and pseudo-anonymizing emails in order to meet legal, personal, acceptability and social constraints. this comprises the use of models for named entity recognition (ner), rule-based systems and their evaluation. in the upcoming sections, we will present research works on corpus building and constraints related to it. ## related work building a corpus is a prerequisite step to various research work in different fields such as discourse analysis, automatic translation and transcription, image recognition, emails segmentation, named entities recognition, etc. @xcite built the comere corpus for discourse analysis and carried out linguistic studies of idiolects that appear in different types of cmc. the comere corpus consists of heterogeneous cmc in french including 3 million chats, 44k sms, 2,030 emails, 2,700 forum messages and 34k tweets. automatically classifying emails in specific email directories and extracting information from them are issues that led to the creation of the en-ron corpus by @xcite , a corpus of emails in english from a private company. the enron corpus has been widely used: email formalities in work environments are studied by @xcite , also @xcite quantify the feelings and tone used in emails. in order to disentangle conversations in the same message stream, @xcite developed a large corpus of 77,563 messages including 74,963 from ubuntu's internet relay chat (irc) channel and 2,600 messages from linux's that highly contribute to research in dialogue analysis. recently, @xcite developed the largest corpus available named webis gmane email corpus 2019 consisting of 153 million emails extracted from 14,669 mailing lists. this corpus data exists in three major languages: english, german and french. these emails are segmented into 15 classes of emails by a neural model with a performance of 96%. as a whole, the scarcity of reference data in general and in particular for the french language justifies our approach to build a corpus that covers the need of thread analysis in cmc context. ## constraints: legal, personal and psychological certain conditions govern the exploitation of public data, including forum, mailing list or web site data. these types of conditions are generally displayed to and agreed upon by the user when registering for these forums and or mailing lists. mentions contained in these terms and conditions often refer to the exploitation of user data for the purposes of training, service improvements and or advertising. unlike this process of joining forums, mailing lists or websites, employees in corporate do not always have to explicitly validate such conditions, but are required to keep secret certain company information on the one hand and on the other hand the private information exchanged in corporate via cmc are governed by the secrecy of correspondence and the general data protection regulation (gdpr) adopted in 2016 and became effective on 25 may 2018 in the european union. personal data protection concerns have been elicited since 1970 @xcite , with ann cavoukain, the privacy commissioner of ontario, canada, co-author of the 1995 international report on privacy enhancing technologies (pet) acting as a forerunner in the domain of data privacy in any technological design. @xcite further clarified that "the future of privacy cannot be assured solely by compliance with regulatory frameworks; rather, privacy assurance must ideally become an organization's default mode of operation". with regard to the secrecy of correspondence, it would be a violation if a third party managed to access even a conversation of collaborators without their consent. our goal of disentangling forum conversations, chats and corporate emails could only be carried out under the respect of the secrecy of correspondence. thus obliging us to submit consent requests to the various collaborators involved in these conversations. this is a tedious task given the number of collaborators in the different teams or entities in a company. in the same vein, the gdpr was established in the european union territory to protect personal data. it applies to any organisation, public and private, that processes personal data on its behalf or not, provided that it is established in the territory of the european union, or that its activity directly targets european residents. the gdpr strengthens the obligation of information and transparency towards the persons (collaborators in our case) whose data we process. despite this obligation of transparency towards collaborators, they are able to exercise their rights of refusal, withdrawal (if committed beforehand) of exploitation of their data. secure and substitute some information from this data are part of the conditions to be respected in order to be gdpr compliance. these conditions are binding for the data acquisition process because require to set up stable and streamlined processes that include administrative and material aspects. the two previous forms of constraints put collaborators at the centre of any data acquisition process in a company. they need to know why and how their data will be used. and depending on the answers given to them, they are free to give their consent or not. unwillingness to share their content which potentially includes personal or highly sensitive data, brings out another group of con-straints that are personal, acceptability and even psychological. all these constraints need to be addressed when dealing with business data acquisition and processing. ## methodology and implementation our process is based upon three main stages: collecting conversations, preprocessing them and pseudo-anonymizing sensitive information in these conversations. for the global aim of conversation disentanglement, it is important to mention that the data will be further analysed by a limited number of people from two different teams, one within the company and another the associated public research team. our goal is to process the data, with anonymization or pseudo-anonymization techniques in particular, so that it is not possible for any person outside that team to identify any participant in the conversations nor to be able to detect participants' personal data. in order to verify our compliance with gdpr and the secrecy of correspondences, our project has gone through an internal validation procedure supervised by a legal commission within the company on the basis of a data life-cycle and a completed risk analysis form. the data life-cycle describes in detail which operations would be performed by which person acting with what role. in particular it helped us identify the possible leaks in the process and their potential consequences. it also specifies that before the anonymization or pseudo-anonymization stage, only specific researcher, who bears the role of technical data controller (tdc) -can access the whole collected data on a secure storage device. the other collaborators in the team can only access the data collected from their own computer. this legal commission evaluated defined the process to follow. this process consists first in obtaining a consent from the targeted collaborators. then, once the data has been collected, any text string that directly or indirectly allows identification of a person or access to personal information must either be removed, modified or pseudo-anonymized. it is worth mentioning that the consent provided by the collaborators is valid for a maximum of one year at a time. to obtain collaborators' consent, we produced media content (video and slides) explaining why and how the process of collecting and analysing data would take place. this is to provide transparency, as requested by gdpr. obtaining a collaborator's consent means having him/her sign a document explaining why we want to collect emails he/she is involved in and under what conditions it is done. for covid-19 reasons these documents were signed electronically and stored on a secure file system. ## future work after obtaining pseudo-anonymised data, we will analyze this data in order to approach the problem of threads constitution with its inherent problems including conversation disentanglement, dialog acts identification and text segmentations. to reconstruct conversation threads, @xcite propose an approach that combines similarity calculations of 8 features built from each email. these features actually bring out the context of an email. taking into account the context of messages or emails allowed researchers of yahoo and amazon @xcite to automatically evaluate the semantic relationship between messages within a mailbox. regarding conversation disentanglement, @xcite and @xcite approach chat disentanglement by first using binary classifier and local coherence models one year later. @xcite take advantage of learning language representations to disentangle conversations. compute similarities between messages using a model they name siamese hierarchical convolutional neural network (shcnn) which is a siamese hierarchical convolutional network. segbot was developed by @xcite to propose a solution to the problem of text segmentation. @xcite address text segmentation as a supervised learning problem and present a large dataset for this problem. dialog acts identification could be seen as determining interlocutors intentions within a conversation. @xcite study the identification of intentions in emails in a workplace situation. all these work give us some leads of experience to be carried out very soon with our data in order to approach our problem of threads constitution. ## conclusion in this paper, we presented a method for building corporate corpora including different aspects and steps which allowed the creation of a pipeline to pseudo-anonymise data. such a pipeline is a response to the constraints induced by the gdpr and the secrecy of correspondence compliance. the process we described consists of several steps: first we prospected with our collaborators to obtain their consent agreement, this in order to be gdpr and secrecy of correspondence compliant; second we collected and pre-processed emails from outlook mailboxes; the third step dealt with manual annotation and named entities recognition; fourth, we performed data pseudo-anonymization. during the second step, we developed a tool called outlookscraping that allowed us to collect a first batch of 11k emails on the workstations of 4 close collaborators out of 78 collaborators who gave their consent agreement. all these steps contributed to the production of pseudo-anonymized data that we will use for our future work of thread constitution. for our constitution of threads problem, we will focus on conversations disentanglement, dialog acts identification and text segmentation.