Aspect and Sentiment Unification Model for Twitter Analysis

BACKGROUND Methylphenidate, a stimulant used to treat attention deficit hyperactivity disorder (ADHD), has the potential for nonmedical uses such as study and recreation. In the era of active use of social networking services (SNSs), experience with the nonmedical use or side effects of methylphenidate might be shared on Twitter. OBJECTIVE To analyze monthly tweets about methylphenidate, its nonmedical use and side effects, and user sentiments about methylphenidate. METHODS Tweets mentioning methylphenidate from August 2018 to July 2019 were collected using search terms for methylphenidate and its brand names. Only tweets written in English were included. The monthly number of tweets about methylphenidate and the number of tweets containing keywords related to the nonmedical use and side effects of methylphenidate were analyzed. Precision was calculated as the number of true nonmedical use or side effects divided by the number of tweets containing each keywords. Sentiment analysis was conducted using the text and emoji in tweets, and tweets were categorized as very negative (less than -3), negative (-3 to -1), neutral (0), positive (1 to 3), or very positive (more than 3), depending on the sentiment score. RESULTS A total of 4,169 tweets were ultimately selected for analysis. The number of tweets per month was lowest in August (n=264) and highest in May (n=435). There were 292 (7.0%) tweets about nonmedical uses of methylphenidate. Among those, 200 (4.8%) described use for studying, and 15 (0.4%) described use for recreation. In 91 (2.2%) tweets, snorting methylphenidate was mentioned. Side effects of methylphenidate, mainly poor appetite (n=74, 1.8%) and insomnia (n=54, 1.3%), were reported in 316 (7.6%) tweets. The average sentiment score was 0.027 ± 1.475, and neutral tweets were the most abundant (n=1,593, 38.2%). CONCLUSIONS Tweets about methylphenidate were most abundant in May, mentioned nonmedical use for study or recreation, and contained information about side effects. Analysis of Twitter has the advantage of saving the cost and time needed to conduct a survey, and could help identify nonmedical uses and side effects of drugs.

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Bot Datasets on Twitter: Analysis and Challenges

Applied Sciences ◽

10.3390/app11094105 ◽

2021 ◽

Vol 11 (9) ◽

pp. 4105

Author(s):

Luis Daniel Samper-Escalante ◽

Octavio Loyola-González ◽

Raúl Monroy ◽

Miguel Angel Medina-Pérez

Keyword(s):

Information Exchange ◽

Modern Society ◽

Online News ◽

Social Networking Service ◽

Public And Private ◽

Challenges And Opportunities ◽

Twitter Analysis ◽

Radar Chart ◽

New Challenges ◽

Bot Detection

The reach and influence of social networks over modern society and its functioning have created new challenges and opportunities to prevent the misuse or tampering of such powerful tools of social interaction. Twitter, a social networking service that specializes in online news and information exchange involving billions of users world-wide, has been infested by bots for several years. In this paper, we analyze both public and private databases from the literature of bot detection on Twitter. We summarize their advantages, disadvantages, and differences, recommending which is more suitable to work with depending on the necessities of the researcher. From this analysis, we present five distinct behaviors in automated accounts exhibited across all the bot datasets analyzed from these databases. We measure their level of presence in each dataset using a radar chart for visual comparison. Finally, we identify four challenges that researchers of bot detection on Twitter have to face when using these databases from the literature.

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“At Least until the Second Wave Comes…”: A Twitter Analysis of the NHS and COVID-19 between March and June 2020

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083943 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3943

Author(s):

Kathy McKay ◽

Sarah Wayland ◽

David Ferguson ◽

Jane Petty ◽

Eilis Kennedy

Keyword(s):

Health Care ◽

Social Media ◽

Content Analysis ◽

Well Being ◽

Profound Impact ◽

Time Period ◽

Twitter Analysis ◽

The Uk ◽

Media Narratives ◽

Second Wave

In the UK, tweets around COVID-19 and health care have primarily focused on the NHS. Recent research has identified that the psychological well-being of NHS staff has been adversely impacted as a result of the COVID-19 pandemic. The aim of this study was to investigate narratives relating to the NHS and COVID-19 during the first lockdown (26 March–4 July 2020). A total of 123,880 tweets were collated and downloaded bound to the time period of the first lockdown in order to analyse the real-time discourse around COVID-19 and the NHS. Content analysis was undertaken and tweets were coded to positive and negative sentiments. Five main themes were identified: (1) the dichotomies of ‘clap for carers’; (2) problems with PPE and testing; (3) peaks of anger; (4) issues around hero worship; and (5) hints of a normality. Further research exploring and documenting social media narratives around COVID-19 and the NHS, in this and subsequent lockdowns, should help in tailoring suitable support for staff in the future and acknowledging the profound impact that the pandemic has had.

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PUBLIC UNIVERSITY LIBRARIES AND SOCIAL MEDIA: SOME KEY ISSUES DERIVED FROM TWITTER ANALYSIS

INTED2021 Proceedings ◽

10.21125/inted.2021.1147 ◽

2021 ◽

Author(s):

Berta Tubillejas-Andrés ◽

Amparo Cervera-Taulet ◽

Haydee Calderón García

Keyword(s):

Social Media ◽

Public University ◽

University Libraries ◽

Key Issues ◽

Twitter Analysis

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Twitter Analysis: Studying US Weekly Trends in Work Stress and Emotion

Applied Psychology ◽

10.1111/apps.12065 ◽

2016 ◽

Vol 65 (2) ◽

pp. 355-378 ◽

Cited By ~ 25

Author(s):

Wei Wang ◽

Ivan Hernandez ◽

Daniel A. Newman ◽

Jibo He ◽

Jiang Bian

Keyword(s):

Work Stress ◽

Twitter Analysis

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Twitter Analysis based on Damage Detection and Geoparsing for Event Mapping Management

Future Computing and Informatics Journal ◽

10.54623/fue.fcij.5.1.1 ◽

2020 ◽

Vol 5 (1) ◽

pp. 1-14

Author(s):

Yasmeen Ali Ameen ◽

◽

Khaled Bahnasy ◽

Adel Elmahdy ◽

◽

...

Keyword(s):

Event Detection ◽

Early Event ◽

Message Content ◽

New Approach ◽

Graphical Displays ◽

Crisis Events ◽

Twitter Analysis ◽

One Year ◽

The Impact ◽

Method Approach

Background: Early event detection, monitor, and response can significantly decrease the impact of disasters. Lately, the usage of social media for detecting events has displayed hopeful results. Objectives: for event detection and mapping; the tweets will locate and monitor them on a map. This new approach uses grouped geoparsing then scoring for each tweet based on three spatial indicators. Method/Approach: Our approach uses a geoparsing technique to match a location in tweets to geographic locations of multiple-events tweets in Egypt country, administrative subdivision. Thus, additional geographic information acquired from the tweet itself to detect the actual locations that the user mentioned in the tweet. Results: The approach was developed from a large pool of tweets related to various crisis events over one year. Only all (very specific) tweets that were plotted on a crisis map to monitor these events. The tweets were analyzed through predefined geo-graphical displays, message content filters (damage, casualties). Conclusion: A method was implemented to predict the effective start of any crisis event and an inequity condition is applied to determine the end of the event. Results indicate that our automated filtering of information provides valuable information for operational response and crisis communication

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Understanding Twitter use by major LIS professional organisations in the United States

Journal of Information Science ◽

10.1177/0165551516687701 ◽

2017 ◽

Vol 44 (2) ◽

pp. 165-183 ◽

Cited By ~ 7

Author(s):

Min Zhang ◽

Feng-Ru Sheu ◽

Yin Zhang

Keyword(s):

United States ◽

Science Education ◽

Information Science ◽

American Library Association ◽

The United States ◽

Library And Information Science ◽

Analysis Framework ◽

Network Analytics ◽

User Influence ◽

Twitter Analysis

Although Twitter has been widely adopted by professional organisations, there has been a lack of understanding and research on its utilisation. This article presents a study that looks into how five major library and information science (LIS) professional organisations in the United States use Twitter, including the American Library Association (ALA), Special Libraries Association (SLA), Association for Library and Information Science Education (ALISE), Association for Information Science and Technology (ASIS&T) and the iSchools. Specifically explored are the characteristics of Twitter usage, such as prevalent topics or contents, type of users involved, as well as the user influence based on number of mentions and retweets. The article also presents the network interactions among the LIS associations on Twitter. A systematic Twitter analysis framework of descriptive analytics, content analytics, user analysis and network analytics with relevant metrics used in this study can be applied to other studies of Twitter use.

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