A framework for text mining on Twitter: a case study on joint comprehensive plan of action (JCPOA)- between 2015 and 2019

Behzadidoost, Rashid; Hasheminezhad, Mahdieh; Farshi, Mohammad; Derhami, Vali; Alamiyan-Harandi, Farinaz

doi:10.1007/s11135-021-01239-y

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…Social [19] To make a comparative text mining in 195.649 collected Persian and English tweets about JCPOA (Joint Comprehensive Plan of Action, commonly known as the Iran nuclear deal or Iran deal).…”

Section: Referencementioning

confidence: 99%

Twitter Data Mining for the Diagnosis of Leaks in Drinking Water Distribution Networks

2023

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This article presents a methodology for using data from social networks, specifically from Twitter, to diagnose leaks in drinking water distribution networks. The methodology involves the collection of tweets from citizens reporting leaks, the extraction of information from the tweets, and the processing of such information to run the diagnosis. To demonstrate the viability of this methodology, 358 Twitter leak reports were collected and analyzed in Mexico City from 1 May to 31 December 2022. From these reports, leak density and probability were calculated, which are metrics that can be used to develop forecasting algorithms, identify root causes, and program repairs. The calculated metrics were compared with those calculated through telephone reports provided by SACMEX, the entity that manages water in Mexico City. Results show that metrics obtained from Twitter and phone reports were highly comparable, indicating the usefulness and reliability of social media data for diagnosing leaks.

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Section: Referencementioning

confidence: 99%

Twitter Data Mining for the Diagnosis of Leaks in Drinking Water Distribution Networks

2023

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“…This process was spotted by Rambukkana (2015), who defines hashtags as generated from "nodes in the becoming of distributed discussions" (Rambukkana, 2015, p. 3). The studies that are placed within this field analyse the content of tweets, working on the analysis of the texts (e.g., Behzadidoost et al, 2021), therefore of the textual traces left by users as comments. Others begin to look at how a network of relationships is generated through hashtag streams (e.g., Pilar et al, 2021), then examine which actors and topics are the subject of public debate.…”

Section: Appraisal Of the First Main Streammentioning

confidence: 99%

Research using hashtags: A meta-synthesis

Rocca

Artieri

2022

Front. Sociol.

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In the last 20 years, research using hashtags has grown considerably. The changes that occurred in the digital environment have influenced their diffusion and development. Today, there is considerable research on hashtags, their use, and on hashtag activism. Likewise, there is a growing interest in their descriptive measures and their metrics. This article aimed to provide a review of this area of research and studies to outline the traits of hashtag research, which are yet nascent. To achieve this, we used a meta-study to produce a meta-synthesis capable of bringing out similarities and differences in research using hashtags and identifying spaces for the generation of new knowledge.

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